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Shortest path algorithms
Microsoft Academic Search
Theshortest path problem is considered from a computational point of view. Eight algorithms which solve theshortest path tree problem on directed graphs are presented, together with the results of wide-ranging experimentation designed to compare their relative performances on different graph topologies. The focus of this paper is on the implementation of the different data structures used in the algorithms. A
Giorgio Gallo; Stefano Pallottino
Randomized distributed shortest paths algorithms
This paper is concerned with distributed algorithm for finding shortest paths in an asynchronous communication network. For the problem of Breadth First Search, the best previously known algorithms required either &THgr;(V) time, or &THgr; (E + V · D) communication. We present new algorithm, which requires O(D1+?) time, and O(E1+?) messages, for any ? > 0. (Here, V is number
B. Awerbuch
Another adaptive distributed shortest path algorithm
The authors give a distributed algorithm to compute shortest paths in a network with changing topology. The authors analyze its behavior. The proof of correctness is discussed. It does not suffer from the routing table looping behavior associated with the Ford-Bellman distributed shortest path algorithm although it uses truly distributed processing. Its time and message complexities are evaluated. Comparisons with
Pierre A. Humblet
Shortest paths algorithms: theory and experimental evaluation
We conduct an extensive computational study of shortest paths algorithms, including some very recent algorithms. We also suggest new algorithms motivated by the experimental results and prove interesting theoretical results suggested by the experimental data. Our computational study is based on several natural problem classes which identify strengths and weaknesses of various algorithms. These problem classes and algorithm implementations form
Boris V. Cherkassky; Andrew V. Goldberg; Tomasz Radzikt
Shortest Paths.
ERIC Educational Resources Information Center
There are many uses for the shortest path algorithm presented which are limited only by our ability to recognize when a problem may be converted into the shortest path in a graph representation. (Author/TG)
Shore, M. L.
Faster algorithms for the shortest path problem
Efficient implementations of Dijkstra's shortest path algorithm are investigated. A new data structure, called the radix heap, is proposed for use in this algorithm. On a network with n vertices, m edges, and nonnegative integer arc costs bounded by C, a one-level form of radix heap gives a time bound for Dijkstra's algorithm of O(m + n log C). A
Ravindra K. Ahuja; Kurt Mehlhorn; James B. Orlin; Robert Endre Tarjan
An Appraisal of Some Shortest Path Algorithms.
National Technical Information Service (NTIS)
A critical review of the literature of shortest paths in networks that examines methods for determining (1) the shortest path between two specified nodes; (2) the shortest path between all pairs of nodes; (3) the second, third, etc., shortest path; (4) th...
S. E. Dreyfus
Distributed computation on graphs: shortest path algorithms
We use the paradigm of diffusing computation, introduced by Dijkstra and Scholten, to solve a class of graph problems. We present a detailed solution to the problem of computing shortest paths from a single vertex to all other vertices, in the presence of negative cycles.
K. Mani Chandy; Jayadev Misra
A distributed, loop-free, shortest-path routing algorithm
A new distributed algorithm for the dynamic computation of the shortest paths in a computer network is presented, validated, and analyzed. According to this algorithm, each node maintains the lengths of the shortest path to each network destination and a feasibility vector. Update messages from a node are sent only to its neighbors; each such message contains one or more
Faster Parametric Shortest Path and Minimum Balance Algorithms
We use Fibonacci heaps to improve a parametric shortest path algorithm of Karp and Orlin, and we combine our algorithm and the method of Schneider and Schneider's minimum-balance algorithm to obtain a faster minimum-balance algorithm. For a graph with n vertices and m edges, our parametric shortest path algorithm and our minimum-balance algorithm both run in O(nm + n2 logn)
Neal E. Young; James B. Orlinz
Faster Shortest-Path Algorithms for Planar Graphs
Abstract: We give a linear-time algorithm for single-source shortest paths in planar graphs with nonnegativeedge-lengths. Our algorithm also yields a linear-time algorithm for maximum flow in a planar graphwith the source and sink on the same face.
Monika Rauch Henzinger; Philip N. Klein; Satish Rao; Sairam Subramanian
Efficient Algorithms for Shortest Paths in Sparse Networks
Algorithms for finding shortest paths are presented which are faster than algorithms previously known on networks which are relatively sparse in arcs. Known results which the results of this paper extend are surveyed briefly and analyzed. A new implementation for priority queues is employed, and a class of "arc set partition" algorithms is introduced. For the single source problem on
Donald B. Johnson
Incremental Algorithms for the Single-Source Shortest Path Problem
We consider the problem of updating a single source shortest path tree in either a directed or an undirected graph, with positive real edge weights. Our semidynamic algorithms for the incremental problem (handling edge insertions and cost decrements) work for any graph, but their performances depend on the class of the considered graph. In any case our algorithms have optimal
Daniele Frigioni; Alberto Marchetti-spaccamela; Umberto Nanni
An Improved Physarum polycephalum Algorithm for the Shortest Path Problem
PubMed Central
Shortest path is among classical problems of computer science. The problems are solved by hundreds of algorithms, silicon computing architectures and novel substrate, unconventional, computing devices. Acellular slime mould P. polycephalum is originally famous as a computing biological substrate due to its alleged ability to approximate shortest path from its inoculation site to a source of nutrients. Several algorithms were designed based on properties of the slime mould. Many of the Physarum-inspired algorithms suffer from a low converge speed. To accelerate the search of a solution and reduce a number of iterations we combined an original model of Physarum-inspired path solver with a new a parameter, called energy. We undertook a series of computational experiments on approximating shortest paths in networks with different topologies, and number of nodes varying from 15 to 2000. We found that the improved Physarum algorithm matches well with existing Physarum-inspired approaches yet outperforms them in number of iterations executed and a total running time. We also compare our algorithm with other existing algorithms, including the ant colony optimization algorithm and Dijkstra algorithm.
Wang, Qing; Adamatzky, Andrew; Chan, Felix T. S.; Mahadevan, Sankaran
A Complete Approximation Algorithm for Shortest Bounded-Curvature Paths
We address the problem of finding a polynomial-time approximation scheme for shortest bounded-curvature paths in the presence\\u000a of obstacles. Given an arbitrary environment E\\\\mathcal{E} consisting of polygonal obstacles, two feasible configurations, a length ?, and an approximation factor ?, our algorithm either (i) verifies that every feasible bounded-curvature path joining the two configurations is longer than\\u000a ? or (ii) constructs
Jonathan Backer; David Kirkpatrick
A Shortest Path Algorithm with Constraints in Networks
\\u000a The paper deals with the shortest path problem with Constraints, and it is NP-complete problem. The problem is formulated\\u000a as an optimization model. To solve this model Lagrangean relaxation algorithm is adopted. For the solution of the dual problem\\u000a a subgradient method is used. The general algorithm steps for our problem are presented, and a numerical example on communication\\u000a network
Fanguo He; Kuobin Dai
A Distributed Context-Free Language Constrained Shortest Path Algorithm
Formal language constrained shortest path problems are concerned with finding shortest paths in labeled graphs. These labeled paths have the constraint that the concatenation of labels along a path constitute a valid string in some formal language Lambda over alphabet Sigma. These problems are well studied where the formal language is regular or context-free, and have been used in a
Charles B. Ward; Nathan M. Wiegand; Phillip G. Bradford
Engineering Label-Constrained Shortest-Path Algorithms
We consider a generalization of the shortest-path problem: given an alphabet ?, a graph G whose edges are weighted and ?-labeled, and a regular language L ? ??, the L-constrained shortest-path problem consists of finding a shortest path p in G such that the concatenated labels along p form a word of L. This definition allows to model, e.g., many
Christopher L. Barrett; Keith Bisset; Martin Holzer; Goran Konjevod; Madhav V. Marathe; Dorothea Wagner
Average Network Flow Problem: Shortest Path and Minimum Cost Flow Formulations, Algorithms, Heuristics, and Complexity.
Integrating value focused thinking with the shortest path problem results in a unique formulation called the multiobjective average shortest path problem. We prove this is NP-complete for general graphs. For directed acyclic graphs, an efficient algorithm...
J. D. Jordan
A Decentralized Algorithm for Finding the Shortest Paths in Defense Communications Networks.
This paper presents a decentralized shortest path algorithm which finds the shortest distances between all pairs of nodes without requiring that any particular node have information about the complete topology of the network. The algorithm requires at mos...
J. Y. Yen
A Study on Shortest Path Routing Algorithm on Dataflow Parallel Reconfigurable Processor DAPDNA2
In IP networks, we ordinally use OSPF(Open Shortest Path First) as a routing protocol. OSPF find the shortest path using Dijkstra's Shortest Path Algorithm. Dijkstra's Algorithm is suitable for program counter based CPU, however it is not scalable for the number of nodes in the networks since its computational complexity is O(n2). In this paper, We propose a parallel shortest
Sho SHIMIZU; Yutaka ARAKAWA; Naoaki YAMANAKA; Kosuke SHIBA
k-PathA: k-shortest Path Algorithm
One important aspect of computational systems biology includes the identification and analysis of functional response networks within large biochemical networks. These functional response networks represent the response of a biological system under a particular experimental condition which can be used to pinpoint critical biological processes.For this purpose, we have developed a novel algorithm to calculate response networks as scored\\/weighted sub-graphs
Alexander Ullrich; Christian V. Forst
An Efficient Parallel Algorithm for Shortest Paths in Planar Layered Digraphs
Computing shortest paths in a directed graph has received considerable attention in the sequential RAM model of computation. However, developing a polylog-time parallel algorithm that is close to the sequential optimal in terms of the total work done remains an elusive goal. We present a first step in this direction by giving efficient parallel algorithms for shortest paths in planar
Sairam Subramanian; Roberto Tamassia; Jeffrey Scott Vitter
Approximation Algorithms for Shortest Path Motion Planning (Extended Abstract)
This paper gives approximation algorithms for solvingthe following motion planning problem: Given aset of polyhedral obstacles and points s and t, find ashortest path from s to t that avoids the obstacles.The paths found by the algorithms are piecewise linear,and the length of a path is the sum of the lengthsof the line segments making up the path. Approximationalgorithms will
Kenneth L. Clarkson
Shortcut in the Decomposition Algorithm for Shortest Paths in a Network
The problem considered is that of finding the shortest path between the two nodes of every pair in a large n-node network. A decomposition algorithm is proposed for use when the number of arcs is less than n(n - 1). The network is first decomposed into several overlapping subnetworks. Next, with each subnetwork treated separately, conditional shortest paths are obtained
T. C. Hu; W. T. Torres
Trans-dichotomous Algorithms for Minimum Spanning Trees and Shortest Paths
The fusion tree method is extended to develop a linear-time algorithm for the minimum spanning tree problem and an O(m +n log n\\/log log n) implementation of Dijkstra's shortest-path algorithm for a graph with n vertices and m edges. The shortest-path algorithm surpasses information-theoretic limitations. The extension of the fusion tree method involves the development of a new data structure,
Michael L. Fredman; Dan E. Willard
Greedy partitioned algorithms for the shortest-path problem
SciTech Connect
A partitioned, priority-queue algorithm for solving the single-source best-path problem is defined and evaluated. Finding single-source paths for sparse graphs is notable because of its definite lack of parallelism-no known algorithm are scalable. Qualitatively, they discuss the close relationship between the algorithm and previous work by Quinn, Chikayama, and others. Performance measurements of variations of the algorithm, implemented both in concurrent and imperative programming languages on a shared-memory multiprocessor, are presented. This quantitative analysis of the algorithms provides insights into the tradeoffs between complexity and overhead in graph-searching executed in high-level parallel languages with automatic task scheduling.
Adamson, P.; Tick, E. (Univ. of Oregon (United States))
Faster shortest-path algorithms for planar graphs
We give a linear-time algorithm for single-sourceshortest paths in planar graphs with nonnegative edgelengths.Our algorithm also yields a linear-time algorithmfor maximum flow in a planar graph with thesource and sink on the same face. The previous best algorithmsfor these problemsrequired\\\\Omega\\\\Gammanplog n) timewhere n is the number of nodes in the input graph.For the case where negative edge-lengths are allowed,we give
Philip N. Klein; Satish Rao; Monika Raucht; Sairam Subramanian
An Evaluation of Potentials of Genetic Algorithm in Shortest Path Problem
NASA Astrophysics Data System (ADS)
One of the most typical issues considered in combinatorial systems in transportation networks, is the shortest path problem. In such networks, routing has a significant impact on the network's performance. Due to natural complexity in transportation networks and strong impact of routing in different fields of decision making, such as traffic management and vehicle routing problem (VRP), appropriate solutions to solve this problem are crucial to be determined. During last years, in order to solve the shortest path problem, different solutions are proposed. These techniques are divided into two categories of classic and evolutionary approaches. Two well-known classic algorithms are Dijkstra and A*. Dijkstra is known as a robust, but time consuming algorithm in finding the shortest path problem. A* is also another algorithm very similar to Dijkstra, less robust but with a higher performance. On the other hand, Genetic algorithms are introduced as most applicable evolutionary algorithms. Genetic Algorithm uses a parallel search method in several parts of the domain and is not trapped in local optimums. In this paper, the potentiality of Genetic algorithm for finding the shortest path is evaluated by making a comparison between this algorithm and classic algorithms (Dijkstra and A*). Evaluation of the potential of these techniques on a transportation network in an urban area shows that due to the problem of classic methods in their small search space, GA had a better performance in finding the shortest path.
Hassany Pazooky, S.; Rahmatollahi Namin, Sh; Soleymani, A.; Samadzadegan, F.
Linear-Time Algorithms for Visibility and Shortest Path Problems Inside Triangulated Simple Polygons
Given a triangulation of a simple polygonP, we present linear-time algorithms for solving a collection of problems concerning shortest paths and visibility withinP. These problems include calculation of the collection of all shortest paths insideP from a given source vertexS to all the other vertices ofP, calculation of the subpolygon ofP consisting of points that are visible from a given
Leonidas J. Guibas; John Hershberger; Daniel Leven; Micha Sharir; Robert Endre Tarjan
Soft-decision Decoding of Block Codes using the k Shortest Paths Algorithm
In this paper, we develop a soft-decision decoding algorithm for block codes using the k shortest paths algorithm. The performance of this algorithm is investigated and compared with other decoding schemes. The results show the proposed algorithm gives large gains over the generalised minimum distance (GMD) decoding algorithm and algebraic hard-decision decoding. Further, the proposed algorithm achieves near-MLD performance for
Ismail Shakeel; Alex Grant
A genetic algorithm for shortest path routing problem and the sizing of populations
This paper presents a genetic algorithmic approach to the shortest path (SP) routing problem. Variable-length chromosomes (strings) and their genes (parameters) have been used for encoding the problem. The crossover operation exchanges partial chromosomes (partial routes) at positionally independent crossing sites and the mutation operation maintains the genetic diversity of the population. The proposed algorithm can cure all the infeasible
Chang Wook Ahn; Rudrapatna S. Ramakrishna
Research on the Algorithm for K-Shortest Paths Problem based on A* in Complicated Network
Focusing on the optimization problems about complicated network, this paper presents an algorithm KSPA to solve the K-shortest paths problem in complicated network based on A* algorithm, in which the time cost is taken as target function and the establishment of the target function model is given. Experimental results show the proposed KSPA maintains an excellent efficiency on certain public
Lichao Chen; Jia Liu; Yingjun Zhang; Binhong Xie
Shortest paths on a polyhedron
We present an algorithm for determining the shortest path between a source point and any destination point along the surface of a polyhedron (need not be convex). Our algorithm uses a new approach which deviates from the conventional "continuous Dijkstra" technique. It takes &Ogr;(n2) time and ⊖(n) space to determine the shortest path and to compute the inward layout which
Jindong Chen; Yijie Han
Finding the k Shortest Paths
We describe algorithms for finding the k shortest paths connectinga given pair of vertices in a digraph (allowing cycles). Our algorithmsoutput an implicit representation of the paths as an unordered setin time O(m + n log n + k). The paths can be output in order bylength in total time O(m + n log n + k log k). We
David Eppstein
Linear time algorithms for visibility and shortest path problems inside simple polygons
We present linear time algorithms for solving the following problems involving a simple planar polygon P: (i) Computing the collection of all shortest paths inside P from a given source vertex s to all the other vertices of P; (ii) Computing the subpolygon of P consisting of points that are visible from a segment within P; (iii) Preprocessing P so
Should QoS routing algorithms prefer shortest paths?
Multimedia traffic and real-time e-commerce applications can experience quality degradation in traditional networks such as the Internet. These difficulties can be overcome in networks which feature dynamically set up paths with bandwidth and delay guarantees. The problem of selecting such constrained paths is the task of quality of service (QoS) routing. This paper considers link-state routing, and the choice of
Karol Kowalik; Martin Collier
Shortest-path and minimum-delay algorithms in networks with time-dependent edge-length
In this paper the shortest-path problem in networks in which the delay (or weight) of the edges changes with time according to arbitrary functions is considered. Algorithms for finding the shortest path and minimum delay under various waiting constraints are presented and the properties of the derived path are investigated. It is shown that if departure time from the source
Ariel Orda; Raphael Rom
Shortest Paths in Euclidean Graphs
We analyze a simple method for finding shortest paths inEuclidean graphs (where vertices are points in a Euclidean space and edge weights are Euclidean distances between points). For many graph\\u000a models, the average running time of the algorithm to find the shortest path between a specified pair of vertices in a graph\\u000a withV vertices andE edges is shown to beO(V)
Robert Sedgewick; Jeffrey Scott Vitter
Fighting organized crimes: using shortest-path algorithms to identify associations in criminal networks
Effective and efficient link analysis techniques are needed to help law enforcement and intelligence agencies fight organized crimes such as narcotics violation, terrorism, and kidnapping. In this paper, we propose a link analysis technique that uses shortest-path algorithms, priority-first-search (PFS) and two-tree PFS, to identify the strongest association paths between entities in a criminal network. To evaluate effectiveness, we compared
Jennifer Jie Xu; Hsinchun Chen
Efficient Parallel Algorithms for Computing All Pair Shortest Paths in Directed Graphs
We present parallel algorithms for computing all pair shortest paths in directed graphs. Our algorithm has time complexity O. f.n\\/= pC I.n\\/ log n\\/ on the PRAM using p processors, where I.n\\/ is log n on the EREW PRAM, log logn on the CCRW PRAM, f.n\\/ is o.n3\\/. On the randomized CRCW PRAM we are able to achieve time complexity
Yijie Han; Victor Y. Pan; John H. Reif
Prediction of Transitive Co-expressed Genes Function by Shortest-Path Algorithm
\\u000a The present paper predicted the function of unknow genes by analyzing the co-expression data of Arabidopsis thaliana from biological pathway based on the shortest-path algorithm. This paper proposed that transitive co-expression among genes\\u000a can be used as an important attribute to link genes of the same biological pathway. The genes from the same biological pathway\\u000a with similar functions are strongly
Huang JiFeng
Discrete Dynamic Shortest Path Problems in Transportation Applications: Complexity and Algorithms with Optimal Run Time
Abstract: This paper solves what appears to be a 30 years old problem dealing with the discovery of most efficient algorithms possible to compute all-to-one shortest paths in discrete dynamic,networks. This problem lies at the heart of efficient solution approaches to dynamic network models that arise in dynamic transportation systems, such as Intelligent Transportation Systems (ITS), applications. While the main
Ismail Chabini
An Improved Ant Colony Algorithm for the Shortest Path Problem in Time-Dependent Networks
Research of the shortest path problem in time-dependent networks has important practical value. An improved pheromone update strategy suitable for time-dependent networks was proposed. Under this strategy, the residual pheromone of each road can accurately reflect the change of weighted value of each road. An improved selection strategy between adjacent cities was used to compute the cities' transfer probabilities, as a result, the amount of calculation is greatly reduced. To avoid the algorithm converging to the local optimal solution, the ant colony algorithm was combined with genetic algorithm. In this way, the solutions after each traversal were used as the initial species to carry out single-point crossover. An improved ant colony algorithm for the shortest path problem in time-dependent networks based on these improved strategies was presented. The simulation results show that the improved algorithm has greater probability to get the global optimal solution, and the convergence rate of algorithm is better than traditional ant colony algorithm.
Chang, Qing; Liu, Yongqiang; Xiong, Huagang
A branch and bound algorithm for the robust shortest path problem with interval data
Many real problems in transportation and telecommunications can be modelled in mathematical terms as shortest path problems on in- terval digraphs, where an interval of costs is associated with each arc. Intervals represent uncertainty, typical of real situations, about the exact values of costs. In this context, a robust shortest path is a path which is ideally not too far
R. Montemanni; L. M. Gambardella; A. E. Rizzoli; A. V. Donati
Many real problems in transportation and telecommunications can be modelled in mathematical terms as shortest path problems on interval digraphs, where an interval cost is associated with each arc. Intervals represent uncertainty, typical of real situations, about the exact values of costs. A robust shortest path is a path which is not too far from the best one, whatever the
Roberto Montemanni; Luca Maria Gambardella; Alberto V. Donati
Parallel shortest augmenting path algorithm for the assignment problem. Technical report
We describe a parallel version of the shortest augmenting path algorithm for the assignment problem. While generating the initial dual solution and partial assignment in parallel does not require substantive changes in the sequential algorithm, using several augmenting paths in parallel does require a new dual variable recalculation method. The parallel algorithm was tested on a 14-processor Butterfly Plus computer, on problems with up to 900 million variables. The speedup obtained increases with problem size. The algorithm was also embedded into a parallel branch and bound procedure for the traveling salesman problem on a directed graph, which was tested on the Butterfly Plus on problems involving up to 7,500 cities. To our knowledge, these are the largest assignment problems and traveling salesman problems solved so far.
Balas, E.; Miller, D.; Pekny, J.; Toth, P.
A comparison of two new exact algorithms for the robust shortest path problem
Real road networks can be modelled in mathematical terms as interval digraphs, where an interval of travel times (costs) is associated with each arc. Intervals represent uncer- tainty, typical of real situations, about exact travel times. A robust shortest path is a path which is not too far from the shortest one, whatever the exact values of arc costs are.
Roberto Montemanni; Luca Maria; Gambardella Alberto Donati
Shortest Paths for Line Segments
Abstract We study the problem of shortest paths for a line segment in the plane. As a measure of the distance traversed by a path, we take the average curve length of the orbits of prescribed points on the line segment. This problem is nontrivial even in free space (i.e., in the absence of obstacles). We characterize all shortest paths
Christian Icking; Giinter Rote; Emo Welzl; Chee-keng Yap
Genetic algorithms with elitism-based immigrants for dynamic shortest path problem in mobile ad hoc networks
In recent years, the static shortest path (SP) problem has been well addressed using intelligent optimization techniques, e.g., artificial neural networks (ANNs), genetic algorithms (GAs), particle swarm optimization (PSO), etc. However, with the advancement in wireless communications, more and more mobile wireless networks appear, e.g., mobile ad hoc network (MANET), wireless sensor network (WSN), etc. One of the most important
Hui Cheng; Shengxiang Yang
Genetic Algorithms With Immigrants and Memory Schemes for Dynamic Shortest Path Routing Problems in Mobile Ad Hoc Networks
In recent years, the static shortest path (SP) problem has been well addressed using intelligent optimization techniques, e.g., artificial neural networks, genetic algorithms (GAs), particle swarm optimization, etc. However, with the advancement in wireless communications, more and more mobile wireless networks appear, e.g., mobile networks [mobile ad hoc networks (MANETs)], wireless sensor networks, etc. One of the most important characteristics
Shengxiang Yang; Hui Cheng; Fang Wang
Shortest Paths Without a Map
Papadimitriou, C.H. and M. Yannakakis, Shortest paths without a map, Theoretical Computer Science 84 (1991) 127-150. We study several versions of the shortest-path problem when the map is not known in advance, but is specified dynamically. We are seeking dynamic decision rules that optimize the worst-case ratio of the distance covered to the length of the (statically) optimal path. We
Christos H. Papadimitriou; Mihalis Yannakakis
Highway Hierarchies Hasten Exact Shortest Path Queries
\\u000a We present a new speedup technique for route planning that exploits the hierarchy inherent in real world road networks. Our\\u000a algorithm preprocesses the eight digit number of nodes needed for maps of the USA or Western Europe in a few hours using linear\\u000a space. Shortest (i.e. fastest) path queries then take around eight milliseconds to produce exact shortest paths. This
Peter Sanders; Dominik Schultes
A Simpler Algorithm for the All Pairs Shortest Path Problem with O(n 2logn) Expected Time
The best known expected time for the all pairs shortest path problem on a directed graph with non-negative edge costs is O(n 2logn) by Moffat and Takaoka. Let the solution set be the set of vertices to which the given algorithm has established shortest paths. The Moffat-Takaoka algorithm maintains complexities before and after the critical point in balance, which is the moment when the size of the solution set is n - n/logn. In this paper, we remove the concept of critical point and the data structure, called a batch list, whereby we make the algorithm simpler and seamless, resulting in a simpler analysis and speed-up.
Takaoka, Tadao; Hashim, Mashitoh
An Incremental Algorithm for a Generalization of the Shortest-Path Problem
Abstract: The grammar problem, a generalization of the single-source shortest-path problem introduced by Knuth, is to computethe minimum-cost derivation of a terminal string from each non-terminal of a given context-free grammar, with the costof a derivation being suitably defined. This problem also subsumes the problem of finding optimal hyperpaths indirected hypergraphs (under varying optimization criteria) that has received attention recently.
G. Ramalingam; Thomas W. Reps
Application of Single-Source Shortest Path Algorithms to an OJCS (Organization of the Joint Chiefs of Staff) Contingency Planning Model and a Vehicle Routing Model.
This thesis investigates the use of single-source shortest path algorithms in two unrelated contexts. In the first application, the label setting and label correcting algorithms are examined for applicability to and implementation with a J-8, Organization...
J. W. Brown
Multi-population Genetic Algorithms with Immigrants Scheme for Dynamic Shortest Path Routing Problems in Mobile Ad Hoc Networks
\\u000a The static shortest path (SP) problem has been well addressed using intelligent optimization techniques, e.g., artificial\\u000a neural networks, genetic algorithms (GAs), particle swarm optimization, etc. However, with the advancement in wireless communications,\\u000a more and more mobile wireless networks appear, e.g., mobile ad hoc network (MANET), wireless mesh network, etc. One of the\\u000a most important characteristics in mobile wireless networks is
Balancing minimum spanning and shortest path trees
This paper give a simple linear-time algorithm that, given a weighted\\u000adigraph, finds a spanning tree that simultaneously approximates a shortest-path\\u000atree and a minimum spanning tree. The algorithm provides a continuous\\u000atrade-off: given the two trees and epsilon > 0, the algorithm returns a\\u000aspanning tree in which the distance between any vertex and the root of the\\u000ashortest-path
Samir Khuller; Balaji Raghavacharit; Neal E. Young
Computing the shortest path: A search meets graph theory
We propose shortest path algorithms that use A* search in combination with a new graph-theoretic lower-bounding technique based on landmarks and the triangle inequality. Our algorithms compute optimal shortest paths and work on any directed graph. We give experimental results showing that the most efficient of our new algorithms outperforms previous algorithms, in particular A* search with Euclidean bounds, by
Andrew V. Goldberg; Chris Harrelson
Algorithms and Bounds for Shortest Paths and Diameter in Faulty Hypercubes
In an n-dimensional hypercube Qn, with the fault set |F|<2n-2, assuming S and D are not isolated, it is shown that there exists a path of length equal to at most their Hamming distance plus 4. An algorithm with complexity O (|F|logn) is given to find such a path. A bound for the diameter of the faulty hypercube Qn-F, when
Sing-ban Tien; C. S. Raghavendra
A study on design of dynamic route guidance system using forecasted travel time based on GPS data and modified shortest path algorithm
The objective of this paper is to propose the design of a dynamic route guidance system using forecasted travel time based on Global Positioning System (GPS) data and a modified shortest path algorithm. The Box-Jenkins method is used to forecast the travel time of each path between network nodes. The Floyd-Warshall algorithm is used to find the optimal route based
Sung-Soo Kim; Jong-Hyun Lee
Large margin shortest path routing
A new discriminative approach to routing inspired by the large margin criterion serving as a basis for support vector machines\\u000a is presented. The proposed formulation uses the benefit of the dualization convex program, and it is possible for standard\\u000a solvers to learn the weighting metrics of the shortest path routing. In order to demonstrate this and due to its simplicity,
Yadamsuren Lutbat; Rentsen Enkhbat; Won-Joo Hwang
Computing shortest paths with comparisons and additions
We present an undirected all-pairs shortest paths (APSP) algorithm which runs on a pointer machine in time O(mn?(m,n)) while making O(mnlog ?(m, n)) comparisons and additions, where m and n are the number of edges and vertices, respectively, and ?(m, n) is Tarjan's inverse-Ackermann function. This improves upon all previous comparison & addition-based APSP algorithms when the graph is sparse,
Seth Pettie; Vijaya Ramachandran
More algorithms for all-pairs shortest paths in weighted graphs
In the first part of the paper, we reexamine the all-pairsshortest paths (APSP) problem and present a newalgorithm with running time approaching O(n3\\/log2n), which improves all known algorithms for general real-weighted dense graphs andis perhaps close to the best result possible without using fast matrix multiplication, modulo a few log log n factors. In the second part of the paper,
Timothy M. Chan
On an instance of the inverse shortest paths problem
The inverse shortest paths problem in a graph is considered, that is, the problem of recovering the arc costs given some information about the shortest paths in the graph. The problem is first motivated by some practical examples arising from applications. An algorithm based on the Goldfarb-Idnani method for convex quadratic programming is then proposed and analyzed for one of
D. Burton; Philippe L. Toint
Identifying the Shortest Path in Large Networks using Boolean Satisfiability
Today, most routing problems are solved using Dijkstra's shortest path algorithm. Many efficient implementations of Dijkstra's algorithm exist and can handle large networks in short runtimes. Despite these advances, it is difficult to incorporate user-specific conditions on the solution when using Dijkstra's algorithm. Such conditions can include forcing the path to go through a specific node, forcing the path to
Fadi A. Aloul; Bashar Al Rawi
A fuzzy shortest path with the highest reliability
This paper concentrates on a shortest path problem on a network where arc lengths (costs) are not deterministic numbers, but imprecise ones. Here, costs of the shortest path problem are fuzzy intervals with increasing membership functions, whereas the membership function of the total cost of the shortest path is a fuzzy interval with a decreasing linear membership function. By the max-min criterion suggested in [R.E. Bellman, L.A. Zade, Decision-making in a fuzzy environment, Management Science 17B (1970) 141-164], the fuzzy shortest path problem can be treated as a mixed integer nonlinear programming problem. We show that this problem can be simplified into a bi-level programming problem that is very solvable. Here, we propose an efficient algorithm, based on the parametric shortest path problem for solving the bi-level programming problem. An illustrative example is given to demonstrate our proposed algorithm.
Keshavarz, Esmaile; Khorram, Esmaile
New Bounds for Old Algorithms: On the Average-Case Behavior of Classic Single-Source Shortest-Paths Approaches
Despite disillusioning worst-case behavior, classic algorithms for single-source shortest-paths (SSSP) like Bellman-Ford are still being used in practice, especially due to their simple data structures. However, surprisingly little is known about the average-case complexity of these approaches. We provide new theoretical and experimental results for the performance of classic label-correcting SSSP algorithms on graph classes with non-negative random edge weights. In particular, we prove a tight lower bound of ?(n 2) for the running times of Bellman-Ford on a class of sparse graphs with O(n) nodes and edges; the best previous bound was ?(n 4/3 - ? ). The same improvements are shown for Pallottino's algorithm. We also lift a lower bound for the approximate bucket implementation of Dijkstra's algorithm from ?(n logn / loglogn) to ?(n 1.2 - ? ). Furthermore, we provide an experimental evaluation of our new graph classes in comparison with previously used test inputs.
Meyer, Ulrich; Negoescu, Andrei; Weichert, Volker
k-Link Shortest Paths in Weighted Subdivisions
We study the shortest path problem in weighted polygonal subdivisions of the plane, with the additional constraint of an upper bound, k, on the number of links (segments) in the path. We prove structural properties of optimal paths and utilize these results to ob- tain approximation algorithms that yield a path having O(k) links and weighted length at most (1
Ovidiu Daescu; Joseph S. B. Mitchell; Simeon C. Ntafos; James D. Palmer; Chee-keng Yap
Critical analysis of hopfield's neural network model for TSP and its comparison with heuristic algorithm for shortest path computation
For shortest path computation, Travelling-Salesman problem is NP-complete and is among the intensively studied optimization problems. Hopfield and Tank's proposed neural network based approach, for solving TSP, is discussed. Since original Hopfield's model suffers from some limitations as the number of cities increase, some modifications are discussed for better performance. With the increase in the number of cities, the best
Farah Sarwar; Abdul Aziz Bhatti
Shortest path and Schramm-Loewner Evolution
We numerically show that the statistical properties of the shortest path on critical percolation clusters are consistent with the ones predicted for Schramm-Loewner evolution (SLE) curves for ? = 1.04 ± 0.02. The shortest path results from a global optimization process. To identify it, one needs to explore an entire area. Establishing a relation with SLE permits to generate curves statistically equivalent to the shortest path from a Brownian motion. We numerically analyze the winding angle, the left passage probability, and the driving function of the shortest path and compare them to the distributions predicted for SLE curves with the same fractal dimension. The consistency with SLE opens the possibility of using a solid theoretical framework to describe the shortest path and it raises relevant questions regarding conformal invariance and domain Markov properties, which we also discuss.
Pose, N.; Schrenk, K. J.; Araujo, N. A. M.; Herrmann, H. J.
Energy efficient dynamic shortest path routing in wireless Ad hoc sensor networks using genetic algorithm
Wireless sensor networks are catching up as the primary mode for monitoring and collecting data in physically challenging environments. They find applications in various fields varying from environment monitoring, military applications to monitoring patients in hospitals. The constraints due to their inherent features make routing in wireless sensor networks a big challenge. This paper covers Genetic algorithm (GA) based simple
R. Nallusamy; K. Duraiswamy; D. Ayya Muthukumar; C. Sathiyakumar
Finding the K Shortest Loopless Paths in a Network
This paper presents an algorithm for finding the K loopless paths that have the shortest lengths from one node to another node in a network. The significance of the new algorithm is that its computational upper bound increases only linearly with the value of K. Consequently, in general, the new algorithm is extremely efficient as compared with the algorithms proposed
Jin Y. Yen
Asymptotic Optimality of Shortest Path Routing.
Many communication networks use adaptive shortest path routing. By this the authors mean that each network link is periodically assigned a length that depends on its congestion level during the preceding period, and all traffic generated between length up...
E. M. Gafni D. P. Pertsekas
The Number of Shortest Paths in the
\\u000a We enumerate all of the shortest paths between any vertex v and the identity vertex in an (n, k)-star graph by enumerating the minimum factorizations of v in terms of the transpositions corresponding to edges in that graph. This result generalizes a previous one for the star\\u000a graph, and can be applied to obtain the number of the shortest paths
Eddie Cheng; Ke Qiu; Zhi Zhang Shen
Shortest path based splitting line finding for touching cells
A shortest path based algorithm is proposed in this paper to find splitting lines for touching cells. Firstly, an initial splitting line is obtained through the distance transform of a marker image and the watershed algorithm. Then, the initial splitting line is separated into different line segments if necessary, and the start and end points of these line segments act as the start and end points of shortest path. Finally, the shortest path algorithm is used to find the splitting line between the start and end points, and the final result of touching cells splitting can be formed by the contour of the touching cells and the splitting lines. Experimental results show that the proposed algorithm is efficient for different types of touching cells.
Bai, Xiangzhi; Sun, Changming; Wang, Peng; Zhou, Fugen
Shortest Paths to Obstacles for a Polygonal Dubins Car
In this paper, we characterize the time-optimal trajectories leading a Dubins car in collision with the obstacles in its workspace. Due to the constant velocity constraint characterizing the Dubins car model, these trajectories form a sufficient set of shortest paths between any robot configuration and the obstacles in the environment. Based on these paths, we define and give the algorithm
Paolo Robuffo Giordano; Marilena Vendittelli
Approximate Shortest Paths Guided by a Small Index
Distance oracles and graph spanners are excerpts of a graph that allow to compute approximate shortest paths. Here, we consider the situation where it is possible to access the original graph in addition to the graph excerpt while computing paths. This allows for asymptotically much smaller excerpts than distance oracles or spanners. The quality of an algorithm in this setting
Jörg Derungs; Riko Jacob; Peter Widmayer
Approximating weighted shortest paths on polyhedral surfaces
IntroductionShortest path problems are among the fundamental problemsstudied in computational geometry. In this video,we consider the problem of computing a shortest costpath between two points s and t on a (possibly nonconvex)polyhedral surface P. The surface is composedof triangular regions (faces) in which each region has anassociated positive weight. The cost of travel througheach region is the distance traveled times
Mark Lanthier; Anil Maheshwari; Jörg-Rüdiger Sack
Stochastic shortest path with unlimited hops
We present new results for the Stochastic Shortest Path problem when an unlimited number of hops may be used. Nodes and links in the network may be congested or uncongested, and their states change over time. The goal is to adaptively choose the next node to visit such that the expected cost to the destination is minimized. Since the state
Ananya Das; Charles U. Martel
Randomized Shortest-Path Problems: A first study
Suppose you have to route agents through a network from a source node to a destination node in some optimal way; for instance by minimizing the total travel cost. Nothing new up to now - you could use a standard shortest- path algorithm. Suppose, however, that you want to avoid pure deterministic routing policies in order, for instance, to allow
Marco Saerens; Luh Yen; Francois Fouss; Youssef Achbany
Visibility graphs and obstacle-avoiding shortest paths
Summary Two closely related problems in Computational Geometry are determining visibility graphs and shortest paths in a two- or three-dimensional environment containing obstacles. Applications are within Computer Graphics and Robotics. We give a survey on recent research done on efficient algorithms for these problems.
H. Alt; E. Welzl
Dynamic shortest path in stochastic traffic networks based on fluid neural network and Particle Swarm Optimization
The shortest path algorithm is critical for dynamic traffic assignment and for the realization of route guidance in intelligent transportation systems (ITS). In this paper, a hybrid Particle Swarm Optimization (PSO) algorithm combined fluid neural network (FNN) to search for the shortest path in stochastic traffic networks is introduced. The algorithm overcomes the weight coefficient symmetry restrictions of the traditional
Yanfang Deng; Hengqing Tong; Xiedong Zhang
Distance oracles and graph spanners are excerpts of a graph that allow to compute approximate shortest paths. Here, we consider\\u000a the situation where it is possible to access the original graph in addition to the graph excerpt while computing paths. This\\u000a allows for asymptotically much smaller excerpts than distance oracles or spanners. The quality of an algorithm in this setting
On shortest paths in polyhedral spaces
We consider the problem of computing the shortest path between two points in two- or three-dimensional space bounded by polyhedral surfaces. In the 2-D case the problem is easily solved in time O(n2 log n).In the general 3-D case the problem is quite hard to solve, and is not even discrete; we present a doubly-exponential procedure for solving the discrete
Amir Schorr
DT-MRI fiber tracking: a shortest paths approach.
We derive a new fiber tracking algorithm for DT-MRI that parts with the locally "greedy" paradigm intrinsic to conventional tracking algorithms. We demonstrate the ability to precisely reconstruct a diverse range of fiber trajectories in authentic and computer-generated DT-MRI data, for which well-known conventional tracking algorithms are shown to fail. Our approach is to pose fiber tracking as a problem in computing shortest paths in a weighted digraph. Voxels serve as vertices, and edges are included between neighboring voxels. We assign probabilities (weights) to edges using a Bayesian framework. Higher probabilities are assigned to edges that are aligned with fiber trajectories in their close proximity. We compute optimal paths of maximum probability using computationally scalable shortest path algorithms. The salient features of our approach are: global optimality--unlike conventional tracking algorithms, local errors do not accumulate and one "wrong-turn" does not spell disaster; a target point is specified a priori; precise reconstruction is demonstrated for extremely low signal-to-noise ratio; impartiality to which of two endpoints is used as a seed; and, faster computation times than conventional all-paths tracking. We can use our new tracking algorithm in either a single-path tracking mode (deterministic tracking) or an all-paths tracking mode (probabilistic tracking). PMID:18815098
Zalesky, Andrew
The weighted region problem: finding shortest paths through a weighted planar subdivision
The problem of determining shortest paths through a weighted planar polygonal subdivision with n vertices is considered. Distances are measured according to a weighted Euclidean metric: The length of a path is defined to be the weighted sum of (Euclidean) lengths of the subpaths within each region. An algorithm that constructs a (restricted) "shortest path map" with respect to a
Joseph S. B. Mitchell; Christos H. Papadimitriou
Neural networks for shortest path computation and routing in computer networks
The application of neural networks to the optimum routing problem in packet-switched computer networks, where the goal is to minimize the network-wide average time delay, is addressed. Under appropriate assumptions, the optimum routing algorithm relies heavily on shortest path computations that have to be carried out in real time. For this purpose an efficient neural network shortest path algorithm that
Mustafa K. Mehmet Ali; Faouzi Kamoun
Undirected single-source shortest paths with positive integer weights in linear time
The single-source shortest paths problem (SSSP) is one of the classic problems in algorithmic graph theory: given a positively weighted graph G with a source vertex s, find the shortest path from s to all other vertices in the graph.Since 1959, all theoretical developments in SSSP for general directed and undirected graphs have been based on Dijkstra's algorithm, visiting the
Mikkel Thorup
An applicable method for solving the shortest path problems
A theorem of Hardy, Littlewood, and Polya, first time is used to find the variational form of the well known shortest path problem, and as a consequence of that theorem, one can find the shortest path problem via quadratic programming. In this paper, we use measure theory to solve this problem. The shortest path problem can be written as an
M. Zamirian; M. H. Farahi; A. R. Nazemi
Shortest Path First with Emergency Exits
Under heavy and dynamic traffic, the SPF routing algorithm often suffers from wild oscilla- tion and severe congestion, and results in degradation of the network performance. In this paper, we present a new routing algorithm (SPF-EE) which attempts to eliminate the problems associated with the SPF algo- rithm by providing alternate paths as emergency exits. With the SPF-EE algorithm, traffic
Zheng Wang; Jon Crowcroft
A New Necessary Condition for Shortest Path Routing
In shortest path routing, traffic is routed along shortest paths defined by link weights. However, not all path systems are feasible in that they can be realized in this way. This is something which needs to be taken into account when searching for a set of paths that minimize capacity consumption. In this paper, we discuss a new necessary condition
Mats Petter Pettersson; Krzysztof Kuchcinski
Using Edge-Valued Decision Diagrams for Symbolic Generation of Shortest Paths
We present a new method for the symbolic construction of shortest paths in reachability graphs. Our algorithm relies on a variant of edge{valued decision diagrams that supports ecien t xed{p oint it- erations for the joint computation of both the reachable states and their distance from the initial states. Once the distance function is known, a shortest path from an
Gianfranco Ciardo; Radu Siminiceanu
On the Shortest Path to Solve the Problem Based on Vague Sets
The shortest path problem (SPP) is currently being greatly studied in fuzzy sets and systems area. Previously published algorithms and methods for the fuzzy shortest path problem based on discrete or continuous types fuzzy sets of fuzzy arc lengths. However, to present an arc real length in vague set is more reasonable than in fuzzy set. Moreover,carrying on various kinds
Yaling Dou; Hongxing Guo; Jingli Zhou
All Pairs Shortest Paths for Graphs with Small Integer Length Edges
The authors have solved the all pairs shortest distances (APSD) problem for graphs with integer edge lengths. Our algorithm is subcubic for edge lengths of small (?M) absolute value. In this paper we show how to transform these algorithms to solve the all pairs shortest paths (APSP), in the same time complexity, up to a polylogarithmic factor. Forn=|V| the number
Zvi Galil; Oded Margalit
Shortest paths synthesis for a car-like robot
This paper deals with the complete characterization of the shortest paths for a car-like robot. Previous works have shown that the search for a shortest path may be limited to a simple family of trajectories. Our work completes this study by providing a way to select inside this family an optimal path to link any two configurations. We combine the
P. Soueres; J.-P. Laumond
Shortest path ray tracing with sparse graphs
A technique for improving the efficiency of shortest path ray tracing (SPR) is presented. The authors analyze situations where SPR fails and provide quantitative measures to assess the performance of SPR ray tracing with varying numbers of nodes. Their improvements include perturbing the ray at interfaces according to Snell's Law, and a method to find correct rays efficiently in regions of low velocity contract. This approach allows the investigator to use fewer nodes in the calculation, thereby increasing the computational efficiency. In two-dimensional (2-D) cross-borehole experiments they find that with their improvements, they need only use 2/3 as many nodes, saving up to 60 percent in time. Savings should be even greater in three dimensions. These improvements make SPR more attractive for tomographic applications in three dimensions.
Fischer, R.; Lees, J.M. (Yale Univ., New Haven, CT (United States). Dept. of Geology and Geophysics)
Witnesses for Boolean Matrix Multiplication and for Shortest Paths
The subcubic methods to compute the shortest distances between all pairs of vertices also do not provide for witnesses; namely they compute the shortest distances but do not generate information for computing quickly the paths themselves. A witness for a shortest path from vi to vj is an index k such that vk is the rst vertex on such a
Noga Alon; Zvi Galilt; Oded Margalit; Moni Naor
Vickrey Prices and Shortest Paths: What is an Edge Worth?
We solve a shortest path problem that is motivated by recent interest in pricing networks or other computational resources. Informally, how much is an edge in a network worth to a user who wants to send data between two nodes along a shortest path? If the network is a decentralized en- tity, such as the Internet, in which multiple self-interest
John Hershberger; Subhash Suri
Fast and accurate estimation of shortest paths in large graphs
Computing shortest paths between two given nodes is a fundamental operation over graphs, but known to be nontrivial over large disk-resident instances of graph data. While a number of techniques exist for answering reachability queries and approximating node distances efficiently, determining actual shortest paths (i.e. the sequence of nodes involved) is often neglected. However, in applications arising in massive online
Andrey Gubichev; Srikanta J. Bedathur; Stephan Seufert; Gerhard Weikum
Expected shortest paths in dynamic and stochastic traffic networks
The dynamic and stochastic shortest path problem (DSSPP) is defined as finding the expected shortest path in a traffic network where the link travel times are modeled as a continuous-time stochastic process. The objective of this paper is to examine the properties of the problem and to identify a technique that can be used to solve the DSSPP given information
Liping Fu; L. R. Rilett
Shortest path algorithms are a key element of many graph problems. They are used in such applications as online direction finding and navigation, as well as modeling of traffic for large scale simulations of major metropolitan areas. As the shortest path algorithms are an execution bottleneck, it is beneficial to move their execution to parallel hardware such as Field-Programmable Gate Arrays (FPGAs). Hardware implementation is accomplished through the use of a small A core replicated on the order of 20 times on an FPGA device. The objective is to maximize the use of on-board random-access memory bandwidth through the use of multi-threaded latency tolerance. Each shortest path core is responsible for one shortest path calculation, and when it is finished it outputs its result and requests the next source from a queue. One of the innovations of this approach is the use of a small bubble sort core to produce the extract-min function. While bubble sort is not usually considered an appropriate algorithm for any non-trivial usage, it is appropriate in this case as it can produce a single minimum out of the list in O(n) cycles, whwere n is the number of elements in the vertext list. The cost of this min operation does not impact the running time of the architecture, because the queue depth for fetching the next set of edges from memory is roughly equivalent to the number of cores in the system. Additionally, this work provides a collection of simulation results that model the behavior of the node queue in hardware. The results show that a hardware queue, implementing a small bubble-type minimum function, need only be on the order of 16 elements to provide both correct and optimal paths. Because the graph database size is measured in the hundreds of megabytes, the Cray SRAM memory is insufficient. In addition to the A* cores, they have developed a memory management system allowing round-robin servicing of the nodes as well as virtual memory managed over the Hypertransport bus. With support for a DRAM graph store with SRAM-based caching on the FPGA, the system provides a speedup of roughly 8.9x over the CPU-based implementation.
BAKER, ZACHARY K. [Los Alamos National Laboratory; GOKHALE, MAYA B. [Los Alamos National Laboratory
All pairs shortest paths using bridging sets and rectangular matrix multiplication
We present two new algorithms for solving the All Pairs Shortest Paths (APSP) problem for weighted directed graphs. Both algorithms use fast matrix multiplication algorithms.The first algorithm solves the APSP problem for weighted directed graphs in which the edge weights are integers of small absolute value in Ő(n2+?) time, where ? satisfies the equation ?(1, ?, 1) = 1 +
Uri Zwick
A temporal ant colony optimization approach to the shortest path problem in dynamic scale-free networks
A large number of networks in the real world have a scale-free structure, and the parameters of the networks change stochastically with time. Searching for the shortest paths in a scale-free dynamic and stochastic network is not only necessary for the estimation of the statistical characteristics such as the average shortest path length of the network, but also challenges the traditional concepts related to the "shortest path" of a network and the design of path searching strategies. In this paper, the concept of shortest path is defined on the basis of a scale-free dynamic and stochastic network model, and a temporal ant colony optimization (TACO) algorithm is proposed for searching for the shortest paths in the network. The convergence and the setup for some important parameters of the TACO algorithm are discussed through theoretical analysis and computer simulations, validating the effectiveness of the proposed algorithm.
Yu, Feng; Li, Yanjun; Wu, Tie-Jun
This paper is devoted to the study of labelling techniques for solving the multi-objective shortest path problem (MSPP) which is an extension of the shortest path problem (SPP) resulting from considering simultaneously more than one cost function (criteria) for the arcs. The generalization of the well known SPP labelling algorithm for the multi- objective situation is studied in detail and
Optimal shortest path queries in a simple polygon
Let P be a simple polygon with n sides. This paper shows how to preprocess the polygon so that, given two query points p and q inside P, the length of the shortest path inside the polygon from p to q can be found in time &Ogr;(log n). The path itself must be polygonal and can be extracted in additional
Leonidas J. Guibas; John Hershberger
Valid Inequalities for a Shortest-Path Routing Optimization Problem
In autonomous systems of the Internet packets are routed on shortest paths to their destinations, for example according to the ECMP principle. The problem of finding a feasible traffic routing configuration realized on paths which can be generated by a system of weights assigned to IP links is NP-hard. This problem can be formulated as a mixed-integer program and attempted
M. Dzida; M. Mycek; M. Zago
Texture recognition by the shortest path on 3D discrete gray-level surface
In this paper, we apply geodesic paths (the shortest path which is an important object in the task of 3D shape analysis) to the description of natural textures. We first introduce an approach called propagation algorithm to estimate the shortest paths on discrete surfaces and then derive a set of texture features (LR, PLR, SDR, DIF and 1c) from them. The results of the experiments indicate that these features can reflect texture surface patterns in various aspects and are suitable for texture description.
Liao, Mengyang; Li, Xinliang; Qin, Jiamei; Wang, Sixian
Three Methods for Optimizing Single-Shortest Path Routing
Intra-domain routing in IP networks is based on the shortest path principle by assigning administrative weights (costs) to links. The resulting least-cost paths determine routes between pairs of routers. If several such equal-cost paths exist between a pair of routers, it may not be clear which of them is actually used to route traffic. This makes it difficult to predict
Mateusz Dzida; M. Zagozdzon; M. Zotkiewicz; M. P. Pettersson; M. Pioro; M. Duelli; M. Menth
Shortest-Path Kernels on Graphs
Data mining algorithms are facing the challenge to deal with an increasing number of complex objects. For graph data, a whole toolbox of data mining algorithms becomes available by defining a kernel function on instances of graphs. Graph kernels based on walks, subtrees and cycles in graphs have been proposed so far. As a general problem, these kernels are either
Karsten M. Borgwardt; Hans-peter Kriegel
Shortest paths of Bounded Curvature in the Plane
Given two oriented points in the plane, we determine and compute the shortest paths of bounded curvature joigning them. This problem has been solved recently, by Dubins in the no-cusp case, and by Reeds and Shepp otherwise. We propose a new solution based on the minimum principle of Pontryagin. Our approach simplifies the proofs and makes clear the global or
Jean-daniel Boissonnat; André Cérézo; Juliette Leblond
Open Shortest Path First (OSPF) Routing Protocol Simulation
Open Shortest Path First (OSPF) is a dynamic, hierarchical routing protocol designed to support routing in TCP\\/IP networks. A simulation of the OSPF Election Protocol shows three results: (1) The Designated Router (DR) can be elected in constant time. (2) If a router has a limited number of input buffers, a competition for buffers between the Election and the Flooding
Deepinder P. Sidhu; Tayang Fu; Shukri Abdallah; Raj Nair; Rob Coltun
Shortest Path Games: Computational Complexity of Solution Concepts
Shortest Path Games: Computational Complexity of Solution Concepts Frank Nebel Abstract: Over the last few years a series of papers has been published that analyse the computational complexity of solution concepts applied to different types of coalitional games, which are expressed by more or less concise representation languages. However, the coalitional games that have been analysed in a computational context
Frank Nebel
Optimal capacity allocation for load balanced shortest path routing
In this paper we first describe the load balanced shortest path routing (LB-SPR) protocol. Then, we present the linear program for the optimal capacity allocation, to minimize the resource consumption when LB-SPR is applied in the network. We show that when the load balancing is applied, the capacity allocation problem can be expressed only in terms of the total traffic
Marija Antic; Aleksandra Smiljanic
Approximate Shortest Path Queries in Graphs Using Voronoi Duals
We propose an approximation method to answer shortest path queries in graphs, based on hierarchical random sampling and Voronoi duals. The lowest level of the hierarchy stores the initial graph. At each higher level, we compute a simplification of the graph on the level below, by selecting a constant fraction of nodes. Edges are generated as the Voronoi dual within
Shinichi Honiden; Michael E. Houle; Christian Sommer; Martin Wolff
Ant colony algorithm for the shortest loop design problem
In this paper, a new algorithm for solving the shortest loop design problem is presented. The shortest loop design problem is to find the shortest loop for an automated guided vehicle covering at least one edge of each department of a block layout. In this paper, first it is shown that this problem can be represented as a graph model.
Kourosh Eshghi; Morteza Kazemi
Approximating Shortest Paths in Large-Scale Networks with an Application to Intelligent Transportation Systems
We propose a hierarchical algorithm for approximating shortest paths between all pairs of nodes in a large-scale network. The algorithm begins by extracting a high-level subnetwork of rela- tively long links (and their associated nodes) where routing decisions are most crucial. This high-level network partitions the shorter links and their nodes into a set of lower-level sub- networks. By fixing
Yu-li Chou; H. Edwin Romeijn; Robert L. Smith
Optimal Shortest Path Queries in a Simple Polygon
Abstract Let P be a simple polygon with n sides. This paper shows how to preprocess,the polygon so that, given two query points p and q inside P, the length of the shortest,path,inside the polygon($#$to q can be found,in time,O(Iogn). The path,itself must,be polygonal and can be extracted,in additional,time proportional,to the number,of turns,it makes.,The preprocessing consists of triangulation,plus a linear
The d-edge shortest-path problem for a Monge graph
A complete edge-weighted directed graph on vertices 1,2,...,n that assigns cost c(i,j) to the edge (i,j) is called Monge if its edge costs form a Monge array, i.e., for all i < k and j < l, c[i, j]+c[k,l]{le} < c[i,l]+c[k,j]. One reason Monge graphs are interesting is that shortest paths can be computed quite quickly in such graphs. In particular, Wilber showed that the shortest path from vertex 1 to vertex n of a Monge graph can be computed in O(n) time, and Aggarwal, Klawe, Moran, Shor, and Wilber showed that the shortest d-edge 1-to-n path (i.e., the shortest path among all 1-to-n paths with exactly d edges) can be computed in O(dn) time. This paper`s contribution is a new algorithm for the latter problem. Assuming 0 {le} c[i,j] {le} U and c[i,j + 1] + c[i + 1,j] {minus} c[i,j] {minus} c[i + 1, j + 1] {ge} L > 0 for all i and j, our algorithm runs in O(n(1 + 1g(U/L))) time. Thus, when d {much_gt} 1 + 1g(U/L), our algorithm represents a significant improvement over Aggarwal et al.`s O(dn)-time algorithm. We also present several applications of our algorithm; they include length-limited Huffman coding, finding the maximum-perimeter d-gon inscribed in a given convex n-gon, and a digital-signal-compression problem.
Bein, W.W. [New Mexico Univ., Albuquerque, NM (United States). Dept. of Computer Science; Larmore, L.L. [California Univ., Riverside, CA (United States). Dept. of Computer Science; Park, J.K. [Sandia National Labs.,Albuquerque, NM (United States)
A Bio-Inspired Method for the Constrained Shortest Path Problem
The constrained shortest path (CSP) problem has been widely used in transportation optimization, crew scheduling, network routing and so on. It is an open issue since it is a NP-hard problem. In this paper, we propose an innovative method which is based on the internal mechanism of the adaptive amoeba algorithm. The proposed method is divided into two parts. In the first part, we employ the original amoeba algorithm to solve the shortest path problem in directed networks. In the second part, we combine the Physarum algorithm with a bio-inspired rule to deal with the CSP. Finally, by comparing the results with other method using an examples in DCLC problem, we demonstrate the accuracy of the proposed method.
Wang, Hongping; Lu, Xi; Wang, Qing
Probabilistic inference and ranking of gene regulatory pathways as a shortest-path problem
Background Since the advent of microarray technology, numerous methods have been devised to infer gene regulatory relationships from gene expression data. Many approaches that infer entire regulatory networks. This produces results that are rich in information and yet so complex that they are often of limited usefulness for researchers. One alternative unit of regulatory interactions is a linear path between genes. Linear paths are more comprehensible than networks and still contain important information. Such paths can be extracted from inferred regulatory networks or inferred directly. Since criteria for inferring networks generally differs from criteria for inferring paths, indirect and direct inference of paths may achieve different results. Results This paper explores a strategy to infer linear pathways by converting the path inference problem into a shortest-path problem. The edge weights used are the negative log-transformed probabilities of directness derived from the posterior joint distributions of pairwise mutual information between gene expression levels. Directness is inferred using the data processing inequality. The method was designed with two goals. One is to achieve better accuracy in path inference than extraction of paths from inferred networks. The other is to facilitate priorization of interactions for laboratory validation. A method is proposed for achieving this by ranking paths according to the joint probability of directness of each path's edges. The algorithm is evaluated using simulated expression data and is compared to extraction of shortest paths from networks inferred by two alternative methods, ARACNe and a minimum spanning tree algorithm. Conclusions Direct path inference appears to achieve accuracy competitive with that obtained by extracting paths from networks inferred by the other methods. Preliminary exploration of the use of joint edge probabilities to rank paths is largely inconclusive. Suggestions for a better framework for such comparisons are discussed.
A new approach to shortest paths on networks based on the quantum bosonic mechanism
This paper presents quantum bosonic shortest path searching (QBSPS), a natural, practical and highly heuristic physical algorithm for reasoning about the recognition of network structure via quantum dynamics. QBSPS is based on an Anderson-like itinerant bosonic system in which a boson's Green function is used as a navigation pointer for one to accurately approach the terminals. QBSPS is demonstrated by rigorous mathematical and physical proofs and plenty of simulations, showing how it can be used as a greedy routing to seek the shortest path between different locations. In methodology, it is an interesting and new algorithm rooted in the quantum mechanism other than combinatorics. In practice, for the all-pairs shortest-path problem in a random scale-free network with N vertices, QBSPS runs in O(?(N) ln ln N) time. In application, we suggest that the corresponding experimental realizations are feasible by considering path searching in quantum optical communication networks; in this situation, the method performs a pure local search on networks without requiring the global structure that is necessary for current graph algorithms.
Jiang, Xin; Wang, Hailong; Tang, Shaoting; Ma, Lili; Zhang, Zhanli; Zheng, Zhiming
Tight analysis of the (1+1)-EA for the single source shortest path problem.
We conduct a rigorous analysis of the (1+1) evolutionary algorithm for the single source shortest path problem proposed by Scharnow, Tinnefeld, and Wegener (The analyses of evolutionary algorithms on sorting and shortest paths problems, 2004, Journal of Mathematical Modelling and Algorithms, 3(4):349-366). We prove that with high probability, the optimization time is O(n2 max{?, log(n)}), where ? is the smallest integer such that any vertex can be reached from the source via a shortest path having at most ? edges. This bound is tight. For all values of n and ? we provide a graph with edge weights such that, with high probability, the optimization time is of order ?(n2 max{?, log(n)}). To obtain such sharp bounds, we develop a new technique that overcomes the coupon collector behavior of previously used arguments. Also, we exhibit a simple Chernoff type inequality for sums of independent geometrically distributed random variables, and one for sequences of random variables that are not independent, but show a desired behavior independent of the outcomes of the previous random variables. We are optimistic that these tools find further applications in the analysis of evolutionary algorithms. PMID:21838552
Doerr, Benjamin; Happ, Edda; Klein, Christian
Pectoral muscle detection in mammograms based on polar coordinates and the shortest path.
The automatic detection and segmentation of the pectoral muscle in the medio-lateral oblique view of mammograms is essential for further analysis of breast anormalies. However, it is still a very difficult task since the sizes, shapes and intensity contrasts of pectoral muscles change greatly from image to image. In this paper, an algorithm based on the shortest path on a graph is proposed to automatically detect the pectoral muscle contour. To overcome the difficulties of searching for the path between a lateral and the top margins of the image, this is first transformed, using polar coordinates. In the transformed image, the muscle boundary in amongst the shortest paths between the top and the bottom rows. A comprehensive comparison with manually-drawn contours reveals the strength of the proposed method. PMID:21096253
Cardoso, Jaime S; Domingues, Ines; Amaral, Igor; Moreira, Ines; Passarinho, Pedro; Santa Comba, Joao; Correia, Ricardo; Cardoso, Maria J
A Graph Search Heuristic for Shortest Distance Paths
This paper presents a heuristic for guiding A* search for finding the shortest distance path between two vertices in a connected, undirected, and explicitly stored graph. The heuristic requires a small amount of data to be stored at each vertex. The heuristic has application to quickly detecting relationships between two vertices in a large information or knowledge network. We compare the performance of this heuristic with breadth-first search on graphs with various topological properties. The results show that one or more orders of magnitude improvement in the number of vertices expanded is possible for large graphs, including Poisson random graphs.
Chow, E
Universal behavior of the shortest-path aggregation
The shortest-path aggregation in a two-dimensional square lattice is studied numerically. We find universal behavior of the cluster formation when the released particles are weakly correlated, and a distinct universal behavior for clusters generated by a strongly correlated release. In particular, we find the fractal dimension {ital D}=1.20{plus minus}0.01 when the released particles are weakly correlated, while a one-dimensional object is obtained when the correlation is strong. We also find the anisotropic exponent {delta}=1.0 in the weak-correlation region.
Wang, X.R.; Wang, X.F. (School of Physics and Astronomy, University of Minnesota, Minneapolis, Minnesota 55455 (United States))
A New Closeness Metric for Social Networks Based on the k Shortest Paths
\\u000a We axiomatically develop a metric of personal connection between individuals in social networks, and construct an optimal\\u000a model to find the best weight of the metric. Our metric optimizes, in some strict-established sense, weighted average of the\\u000a k shortest paths so that it is able to distinguish the closeness between nodes more relevantly than traditional metrics. The\\u000a algorithms are implemented
Chun Shang; Yuexian Hou; Shuo Zhang; Zhaopeng Meng
Fast estimation of diameter and shortest paths (without matrix multiplication)
In the recent past, there has been considerable progress in devising algorithms for the allpairsshortest paths problem running in time significantly smaller than the obvious time bound ofO(n3). Unfortunately, all the new algorithms are based on fast matrix multiplication algorithmsthat are notoriously impractical. Our work is motivated by the goal of devising purely combinatorialalgorithms that match these improved running times.
Donald Aingworth; Chandra Chekuri; Rajeev Motwani
Corridor location: the multi-gateway shortest path model
The problem of corridor location can be found in a number of fields including power transmission, highways, and pipelines. It involves the placement of a corridor or rights-of-way that traverses a landscape starting at an origin and ending at a destination. Since most systems are subject to environmental review, it is important to generate competitive, but different alternatives. This paper addresses the problem of generating efficient, spatially different alternatives to the corridor location problem. We discuss the weaknesses in current models and propose a new approach which is designed to overcome many of these problems. We present an application of this model to a real landscape and compare the results to past work. Overall, the new model called the multi-gateway shortest path problem can generate a wide variety of efficient alignments, which eclipse what could be generated by past work.
Scaparra, Maria P.; Church, Richard L.; Medrano, F. Antonio
Damage detection via shortest-path network sampling
Large networked systems are constantly exposed to local damages and failures that can alter their functionality. The knowledge of the structure of these systems is, however, often derived through sampling strategies whose effectiveness at damage detection has not been thoroughly investigated so far. Here, we study the performance of shortest-path sampling for damage detection in large-scale networks. We define appropriate metrics to characterize the sampling process before and after the damage, providing statistical estimates for the status of nodes (damaged, not damaged). The proposed methodology is flexible and allows tuning the trade-off between the accuracy of the damage detection and the number of probes used to sample the network. We test and measure the efficiency of our approach considering both synthetic and real networks data. Remarkably, in all of the systems studied, the number of correctly identified damaged nodes exceeds the number of false positives, allowing us to uncover the damage precisely.
Ciulla, Fabio; Perra, Nicola; Baronchelli, Andrea; Vespignani, Alessandro
Finding Shortest Paths on Surfaces Using Level Sets Propagation
We present a new algorithm for determining minimal length paths between two regions on a three dimensional surface. The numerical implementation is based on finding equal geodesic distance contours from a given area. These contours are calculated as zero sets of a bivariate function designed to evolve so as to track the equal distance curves on the given surface. The
Ron Kimmel; Arnon Amir; Alfred M. Bruckstein
Size and Weight of Shortest Path Trees with Exponential Link Weights
We derive the distribution of the number of links and the average weight for the shortest path tree (SPT) rooted at an arbitrary node to m uniformly chosen nodes in the complete graph of size N with i.i.d. exponential link weights. We rely on the fact that the full shortest path tree to all destinations (i.e., m = N ?
Remco Van Der Hofstad; Gerard Hooghiemstra; Piet Van Mieghem
Gene Function Prediction with the Shortest Path in Functional Linkage Graph
This paper presents a new technique for gene function prediction with the shortest path in functional linkage graph. With existing protein-protein interaction data, complex data and gene expression data, a weighted functional linkage graph is inferred. By finding the shortest path in the functional linkage graph, the functions of unknown genes can be predicted with the functions of those that
Xing-Ming Zhao; Luonan Chen; Kazuyuki Aihara
Color texture classification using shortest paths in graphs.
Color textures are among the most important visual attributes in image analysis. This paper presents a novel method to analyze color textures by modeling a color image as a graph in two different and complementary manners (each color channel separately and the three color channels altogether) and by obtaining statistical moments from the shortest paths between specific vertices of this graph. Such an approach allows to create a set of feature vectors, which were extracted from VisTex, USPTex, and TC00013 color texture databases. The best classification results were 99.07%, 96.85%, and 91.54% (LDA with leave-one-out), 87.62%, 66.71%, and 88.06% (1NN with holdout), and 98.62%, 96.16%, and 91.34% (LDA with holdout) of success rate (percentage of samples correctly classified) for these three databases, respectively. These results prove that the proposed approach is a powerful tool for color texture analysis to be explored. PMID:24988594
de Mesquita Sa Junior, Jarbas Joaci; Cortez, Paulo Cesar; Backes, Andre Ricardo
Identification of Lung-Cancer-Related Genes with the Shortest Path Approach in a Protein-Protein Interaction Network
Lung cancer is one of the leading causes of cancer mortality worldwide. The main types of lung cancer are small cell lung cancer (SCLC) and nonsmall cell lung cancer (NSCLC). In this work, a computational method was proposed for identifying lung-cancer-related genes with a shortest path approach in a protein-protein interaction (PPI) network. Based on the PPI data from STRING, a weighted PPI network was constructed. 54 NSCLC- and 84 SCLC-related genes were retrieved from associated KEGG pathways. Then the shortest paths between each pair of these 54 NSCLC genes and 84 SCLC genes were obtained with Dijkstra's algorithm. Finally, all the genes on the shortest paths were extracted, and 25 and 38 shortest genes with a permutation P value less than 0.05 for NSCLC and SCLC were selected for further analysis. Some of the shortest path genes have been reported to be related to lung cancer. Intriguingly, the candidate genes we identified from the PPI network contained more cancer genes than those identified from the gene expression profiles. Furthermore, these genes possessed more functional similarity with the known cancer genes than those identified from the gene expression profiles. This study proved the efficiency of the proposed method and showed promising results.
Li, Bi-Qing; You, Jin; Chen, Lei; Zhang, Jian; Zhang, Ning; Li, Hai-Peng; Huang, Tao; Kong, Xiang-Yin; Cai, Yu-Dong
A sieve algorithm for the shortest lattice vector problem
We present a randomized 2^{O(n)} time algorithm to compute a shortest non-zero vector in an n-dimensional rational lattice. The best known time upper bound for this problem was 2^{O(n\\\\log n)} first given by Kannan [7] in 1983. We obtain several consequences of this algorithm for related problems on lattices and codes, including an improvement for polynomial time approximations to the
Miklós Ajtai; Ravi Kumar; D. Sivakumar
A minimum resource neural network framework for solving multiconstraint shortest path problems.
Characterized by using minimum hard (structural) and soft (computational) resources, a novel parameter-free minimal resource neural network (MRNN) framework is proposed for solving a wide range of single-source shortest path (SP) problems for various graph types. The problems are the k-shortest time path problems with any combination of three constraints: time, hop, and label constraints, and the graphs can be directed, undirected, or bidirected with symmetric and/or asymmetric traversal time, which can be real and time dependent. Isomorphic to the graph where the SP is to be sought, the network is activated by generating autowave at source neuron and the autowave travels automatically along the paths with the speed of a hop in an iteration. Properties of the network are studied, algorithms are presented, and computation complexity is analyzed. The framework guarantees globally optimal solutions of a series of problems during the iteration process of the network, which provides insight into why even the SP is still too long to be satisfied. The network facilitates very large scale integrated circuit implementation and adapt to very large scale problems due to its massively parallel processing and minimum resource utilization. When implemented in a sequentially processing computer, experiments on synthetic graphs, road maps of cities of the USA, and vehicle routing with time windows indicate that the MRNN is especially efficient for large scale sparse graphs and even dense graphs with some constraints, e.g., the CPU time taken and the iteration number used for the road maps of cities of the USA is even less than ? 2% and 0.5% that of the Dijkstra's algorithm. PMID:25050952
Zhang, Junying; Zhao, Xiaoxue; He, Xiaotao
Performance of multihop wireless networks: shortest path is not enough
Existing wireless ad hoc routing protocols typically find routes with the minimum hop-count. This paper presents experimental evidence from two wireless test-beds which shows that there are usually multiple minimum hop-count paths, many of which have poor throughput. As a result, minimum-hop-count routing often chooses routes that have significantly less capacity than the best paths that exist in the network.
Douglas S. J. De Couto; Daniel Aguayo; Benjamin A. Chambers; Robert Morris
The approach for shortest paths in fire succor based on component GIS technology
Fire safety is an important issue for the national economy and people's living. Efficiency and exactness of fire department succor directly relate to safety of peoples' lives and property. Many disadvantages of the traditional fire system have been emerged in practical applications. The preparation of pumpers is guided by wireless communication or wire communication, so its real-time and accurate performances are much poorer. The information about the reported fire, such as the position, disaster and map, et al., for alarm and command was processed by persons, which slows the reaction speed and delays the combat opportunity. In order to solve these disadvantages, it has an important role to construct a modern fire command center based on high technology. The construction of modern fire command center can realize the modernization and automation of fire command and management. It will play a great role in protecting safety of peoples' lives and property. The center can enhance battle ability and can reduce the direct and indirect loss of fire damage at most. With the development of science technology, Geographic Information System (GIS) has becoming a new information industry for hardware production, software development, data collection, space analysis and counseling. With the popularization of computers and the development of GIS, GIS has gained increasing broad applications for its strong functionality. Network analysis is one of the most important functions of GIS, and the most elementary and pivotal issue of network analysis is the calculation of shortest paths. The shortest paths are mostly applied to some emergent systems such as 119 fire alarms. These systems mainly require that the computation time of the optimal path should be 1-3 seconds. And during traveling, the next running path of the vehicles should be calculated in time. So the implement of the shortest paths must have a high efficiency. In this paper, the component GIS technology was applied to collect and record the data information (such as, the situation of this disaster, map and road status et al) of the reported fire firstly. The ant colony optimization was used to calculate the shortest path of fire succor secondly. The optimization results were sent to the pumpers, which can let pumpers choose the shortest paths intelligently and come to fire position with least time. The programming method for shortest paths is proposed in section 3. There are three parts in this section. The elementary framework of the proposed programming method is presented in part one. The systematic framework of GIS component is described in part two. The ant colony optimization employed is presented in part three. In section 4, a simple application instance was presented to demonstrate the proposed programming method. There are three parts in this section. The distributed Web application based on component GIS was described in part one. The optimization results without traffic constraint were presented in part two. The optimization results with traffic constraint were presented in part three. The contributions of this paper can be summarized as follows. (1) It proposed an effective approach for shortest paths in fire succor based on component GIS technology. This proposed approach can achieve the real-time decisions of shortest paths for fire succor. (2) It applied the ant colony optimization to implement the shortest path decision. The traffic information was considered in the shortest path decision using ant colony optimization. The final application instance suggests that the proposed approach is feasible, correct and valid.
Han, Jie; Zhao, Yong; Dai, K. W.
Watershed Cuts: Thinnings, Shortest Path Forests, and Topological Watersheds
We recently introduced watershed cuts, a notion of watershed in edge-weighted graphs. In this paper, our main contribution is a thinning paradigm from which we derive three algorithmic watershed cut strategies: The first one is well suited to parallel implementations, the second one leads to a flexible linear-time sequential implementation, whereas the third one links the watershed cuts and the
Jean Cousty; Gilles Bertrand; Laurent Najman; Michel Couprie
Bounded Incremental Single-Source Shortest-Paths
We consider the problem of maintaining the distances of all vertices of a directed graph from a specific vertex, its source. We show algorithms in the bounded incremental computation (BIC) model which handle the insertion or deletion of an arc (or a batch of arcs outgoing from a shared vertex) in O(kk + |?|log |?|) amortized time on Cyclic>0 graphs
Irit Katriel; Pascal Van Hentenryck
Weight of a link in a shortest path tree and the Dedekind Eta function
The weight of a randomly chosen link in the shortest path tree on the complete graph with exponential i.i.d. link weights is studied. The corresponding exact probability generating function and the asymptotic law are derived. As a remarkable coincidence, this asymptotic law is precisely the same as the distribution of the cost of one \\
Piet Van Mieghem
Spatial interpolation of fine particulate matter concentrations using the shortest wind-field path distance.
Effective assessments of air-pollution exposure depend on the ability to accurately predict pollutant concentrations at unmonitored locations, which can be achieved through spatial interpolation. However, most interpolation approaches currently in use are based on the Euclidean distance, which cannot account for the complex nonlinear features displayed by air-pollution distributions in the wind-field. In this study, an interpolation method based on the shortest path distance is developed to characterize the impact of complex urban wind-field on the distribution of the particulate matter concentration. In this method, the wind-field is incorporated by first interpolating the observed wind-field from a meteorological-station network, then using this continuous wind-field to construct a cost surface based on Gaussian dispersion model and calculating the shortest wind-field path distances between locations, and finally replacing the Euclidean distances typically used in Inverse Distance Weighting (IDW) with the shortest wind-field path distances. This proposed methodology is used to generate daily and hourly estimation surfaces for the particulate matter concentration in the urban area of Beijing in May 2013. This study demonstrates that wind-fields can be incorporated into an interpolation framework using the shortest wind-field path distance, which leads to a remarkable improvement in both the prediction accuracy and the visual reproduction of the wind-flow effect, both of which are of great importance for the assessment of the effects of pollutants on human health. PMID:24798197
Li, Longxiang; Gong, Jianhua; Zhou, Jieping
Comparison of k-shortest paths and maximum flow routing for network facility restoration
In the development of technologies for span failure restoration, a question arises about the restoration rerouting characteristics to be specified. In theory, maximal rerouting capacity is obtained with a maximum flow (Max Flow) criterion. However, rerouting that realizes the k-successively shortest link disjoint paths (KSP) may be faster, easier, and, in distributed implementation, more robust than a distributed counterpart for
D. Anthony Dunn; Wayne D. Grover; Mike H. MacGregor
Transitive Functional Annotation by Shortest-path Analysis of Gene Expression Data
attribute to link genes of the same biological pathway. Based on large-scale yeast microarray expression data, we use the shortest-path analysis to identify transitive genes between two given genes from the same biological process. We find that not only functionally related genes with correlated expression profiles are identified but also those without. In the latter case, we compare our method
Xianghong Zhou; Ming-Chih J. Kao; Wing Hung Wong
Partially observed stochastic shortest path problem - application to sequential paging in cellular networks
Polling a roaming mobile user in a cellular network to determine its location is called paging and it requires the use of limited wireless resources. We formulate the paging problem as an optimal sequential search problem for a Markovian target and show that the resulting problem is an instance of a Partially Observed Stochastic Shortest Path (POSSP) problem. Using the
Sumeetpal Singh; Vikram Krishnamurthy
Topology and Shortest Path Length Evolution of The Internet Autonomous Systems Interconnectivity
Connection networks are observed in many areas of human knowledge. The characterization and topological studies of these networks may be performed through distribution of connectivity degrees, rank properties, shortest path length between nodes, adjacency matrix etc. This paper characterizes the Internet con- nections evolution over the last 10 years at the Autonomous Systems (AS) level analyzing the complete BGP data
N. ALVES Jr.; M. P. de ALBUQUERQUE; Xavier Sigaud; J. T. de ASSIS
Shortest Path Cost Distribution in Random Graphs with Positive Integer Edge Costs
The probability distribution of the shortest path cost from a source node to an arbitrary destination node is considered for a random network model consisting of a complete digraph with positive integer random edge costs. Edge costs are chosen according to a common probability distribution for each direction. For this model, the joint distribution of the number of nodes which
Scott K. Walley; Harry H. Tan; Audrey M. Viterbi
There are some ramp entry or exit direction limitations on networks. This kind of limitation is represented by successive passage prohibition (SPP). It indicates that the vehicles cannot successively pass two links with SPP attributes. However, the shortest-path tree sometimes cannot be expressed with a simple tree when a network having this limitation is represented with single nodes. In such
Kazutaka TAKAO; Tohru HIGASHI; Koji YASUDA; Yasuo ASAKURA
Spatial Interpolation of Fine Particulate Matter Concentrations Using the Shortest Wind-Field Path Distance
Effective assessments of air-pollution exposure depend on the ability to accurately predict pollutant concentrations at unmonitored locations, which can be achieved through spatial interpolation. However, most interpolation approaches currently in use are based on the Euclidean distance, which cannot account for the complex nonlinear features displayed by air-pollution distributions in the wind-field. In this study, an interpolation method based on the shortest path distance is developed to characterize the impact of complex urban wind-field on the distribution of the particulate matter concentration. In this method, the wind-field is incorporated by first interpolating the observed wind-field from a meteorological-station network, then using this continuous wind-field to construct a cost surface based on Gaussian dispersion model and calculating the shortest wind-field path distances between locations, and finally replacing the Euclidean distances typically used in Inverse Distance Weighting (IDW) with the shortest wind-field path distances. This proposed methodology is used to generate daily and hourly estimation surfaces for the particulate matter concentration in the urban area of Beijing in May 2013. This study demonstrates that wind-fields can be incorporated into an interpolation framework using the shortest wind-field path distance, which leads to a remarkable improvement in both the prediction accuracy and the visual reproduction of the wind-flow effect, both of which are of great importance for the assessment of the effects of pollutants on human health.
Efficiently Answering Probability Threshold-Based Shortest Path Queries over Uncertain Graphs
\\u000a Efficiently processing shortest path (SP) queries over stochastic networks attracted a lot of research attention as such queries\\u000a are very popular in the emerging real world applications such as Intelligent Transportation Systems and communication networks\\u000a whose edge weights can be modeled as a random variable. Some pervious works aim at finding the most likely SP (the path with\\u000a largest probability
Ye Yuan; Lei Chen; Guoren Wang
Shortest multiple disconnected path for the analysis of entanglements in two- and three-dimensional polymeric systems
We present an algorithm which returns a shortest path and related number of entanglements for a given configuration of a polymeric system in 2 or 3 dimensions. Rubinstein and Helfand, and later Everaers et al. introduced a concept to extract primitive paths for dense polymeric melts made of linear chains (a multiple disconnected multibead 'path'), where each primitive path is defined as a path connecting the (space-fixed) ends of a polymer under the constraint of non-interpenetration (excluded volume) between primitive paths of different chains, such that the multiple disconnected path fulfills a minimization criterion. The present algorithm uses geometrical operations and provides a—model independent—efficient approximate solution to this challenging problem. Primitive paths are treated as 'infinitely' thin (we further allow for finite thickness to model excluded volume), and tensionless lines rather than multibead chains, excluded volume is taken into account without a force law. The present implementation allows to construct a shortest multiple disconnected path (SP) for 2D systems (polymeric chain within spherical obstacles) and an optimal SP for 3D systems (collection of polymeric chains). The number of entanglements is then simply obtained from the SP as either the number of interior kinks, or from the average length of a line segment. Further, information about structure and potentially also the dynamics of entanglements is immediately available from the SP. We apply the method to study the 'concentration' dependence of the degree of entanglement in phantom chain systems. Program summaryTitle of program:Z Catalogue number:ADVG Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADVG Program obtainable from: CPC Program Library, Queen's University of Belfast, N. Ireland Computer for which the program is designed and others on which it has been tested: Silicon Graphics (Irix), Sun (Solaris), PC (Linux) Operating systems or monitors under which the program has been tested: UNIX, Linux Program language used: USANSI Fortran 77 and Fortran 90 Memory required to execute with typical data: 1 MByte No. of lines in distributed program, including test data, etc.: 10 660 No. of bytes in distributed program, including test data, etc.: 119 551 Distribution formet:tar.gz Nature of physical problem: The problem is to obtain primitive paths substantiating a shortest multiple disconnected path (SP) for a given polymer configuration (chains of particles, with or without additional single particles as obstacles for the 2D case). Primitive paths are here defined as in [M. Rubinstein, E. Helfand, J. Chem. Phys. 82 (1985) 2477; R. Everaers, S.K. Sukumaran, G.S. Grest, C. Svaneborg, A. Sivasubramanian, K. Kremer, Science 303 (2004) 823] as the shortest line (path) respecting 'topological' constraints (from neighboring polymers or point obstacles) between ends of polymers. There is a unique solution for the 2D case. For the 3D case it is unique if we construct a primitive path of a single chain embedded within fixed line obstacles [J.S.B. Mitchell, Geometric shortest paths and network optimization, in: J.-R. Sack, J. Urrutia (Eds.), Handbook of Computational Geometry, Elsevier, Amsterdam, 2000, pp. 633-701]. For a large 3D configuration made of several chains, short is meant to be the Euclidean shortest multiple disconnected path (SP) where primitive paths are constructed for all chains simultaneously. While the latter problem, in general, does not possess a unique solution, the algorithm must return a locally optimal solution, robust against minor displacements of the disconnected path and chain re-labeling. The problem is solved if the number of kinks (or entanglements Z), explicitly deduced from the SP, is quite insensitive to the exact conformation of the SP which allows to estimate Z with a small error. Efficient method of solution: Primitive paths are constructed from the given polymer configuration (a non-shortest multiple disconnected path, including obstacles, if present) by first replacing each polymer contour by a line wi
Kröger, Martin
Transmission Scheduling for Sensor Network Lifetime Maximization: A Shortest Path Bandit Formulation
This paper addresses optimal sensor scheduling for maximizing network lifetime. We formulate this problem as a stochastic shortest-path multi-armed bandit problem. The optimal transmission scheduling policy is thus to choose the sensor with the largest Gittins index. Exploiting the underlying structure of the sensor scheduling problem, we derive a closed-form expression for the Gittins index. We show that choosing the
Yunxia Chen; Qing Zhao; Vikram Krishnamurthy; Dejan Djonin
F-TPR: fine two-phase IP routing scheme over shortest paths for hose model
This letter proposes an IP-based finely-distributed routing scheme based on two-phase routing (TPR) over shortest paths for the hose model. It is called the fine-TPR (F-TPR) scheme. Compared to the original TPR, F-TPR distributes traffic from a source node to intermediate nodes more finely, where the distribution ratio is determined for each source-destination pair. To determine an optimum set of
Eiji Oki; Ayako Iwaki
Time-Varying Shortest Path Problems with Perishable Product and Constraints
This paper develops a new version of time-varying shortest path problem. Let G = (V, E) be a directed graph. A set of perishable products will be transferred by vehicles from source s to destination d. Each arc eepsiE has four parameters: transit time b(e, n2, u), transit cost c(e, n2, u), vehicle cost S(e, n2, u, t) and vehicle
Hou. Wenting; Cai Xiaoqiang
Probability distribution of the shortest path on the percolation cluster, its backbone, and skeleton
We consider the mean distribution functions Phi(r\\\\|l), PhiB(r\\\\|l), and PhiS(r\\\\|l), giving the probability that two sites on the incipient percolation cluster, on its backbone and on its skeleton, respectively, connected by a shortest path of length l are separated by an Euclidean distance r. Following a scaling argument due to de Gennes for self-avoiding walks, we derive analytical expressions for
Markus Porto; Shlomo Havlin; H. Eduardo Roman; Armin Bunde
Swapping a Failing Edge of a Single Source Shortest Paths Tree Is Good and Fast
\\u000a \\u000a Abstract. Let G=(V,E) be a 2-edge connected, undirected and nonnegatively weighted graph, and let S(r) be a single source shortest paths tree (SPT) of G rooted at r ? V . Whenever an edge e in S(r) fails, we are interested in reconnecting the nodes now disconnected from the root by means of a single edge e' crossing the
Enrico Nardelli; Guido Proietti; Peter Widmayer
Energy penalties for non-shortest paths in wireless sensor networks with link failures
ABSTRACT This paper addresses the additional energy consumption,in wire- less sensor networks where the communication,between the sensor nodes and the sink nodes does not always make,use of the shortest path, due to the presence of link failures. For simplicity, link fail- ures are assumed,to be stochastic and independent. The basis for the analysis is a planned topology, with multiple sinks
Geir Egeland; Paal E. Engelstad
How to Swap a Failing Edge of a Single Source Shortest Paths Tree
In this paper we introduce the notion of best swap for a failing edge of a single source shortest paths tree (SPT) S(r) rooted in r in a weighted graph G =( V; E). Given an edge e 2 S(r), an edge e0 2 E nfeg is a swap edge if the swap tree Se=e0(r) obtained by swapping e with
On the Approximability of the Minimum Congestion Unsplittable Shortest Path Routing Problem
\\u000a We are given an undirected simple graph G = (V,E) with edge capacities ce e<\\/font\\u000a>Z+c_{e} \\\\epsilon \\\\mathcal{Z}+, e ? E, and a set K???V\\u000a 2 of commodities with demand values d\\u000a (s,t)\\u000a ??, (s, t) ? K. An unsplittable shortest path routing (USPR) of the commodities K is a set of flow paths ?(s,t), (s, t) ? K, such
Andreas Bley
Multiple Waypoint Path Planning for a Mobile Robot using Genetic Algorithms
This investigation developed a MATLAB program, based on genetic algorithms that generated an optimal (shortest distance) path plan for a mobile robot to visit all of the specified waypoints without colliding with the known obstacles. The designed genetic algorithm path planner was shown to accomplish this task and produce superior results when compared against a full search path planner. Next,
Trevor Davies; A. Jnifene
A computational study identifies HIV progression-related genes using mRMR and shortest path tracing.
Since statistical relationships between HIV load and CD4+ T cell loss have been demonstrated to be weak, searching for host factors contributing to the pathogenesis of HIV infection becomes a key point for both understanding the disease pathology and developing treatments. We applied Maximum Relevance Minimum Redundancy (mRMR) algorithm to a set of microarray data generated from the CD4+ T cells of viremic non-progressors (VNPs) and rapid progressors (RPs) to identify host factors associated with the different responses to HIV infection. Using mRMR algorithm, 147 gene had been identified. Furthermore, we constructed a weighted molecular interaction network with the existing protein-protein interaction data from STRING database and identified 1331 genes on the shortest-paths among the genes identified with mRMR. Functional analysis shows that the functions relating to apoptosis play important roles during the pathogenesis of HIV infection. These results bring new insights of understanding HIV progression. PMID:24244287
Ma, Chengcheng; Dong, Xiao; Li, Rudong; Liu, Lei
A Computational Study Identifies HIV Progression-Related Genes Using mRMR and Shortest Path Tracing
Since statistical relationships between HIV load and CD4+ T cell loss have been demonstrated to be weak, searching for host factors contributing to the pathogenesis of HIV infection becomes a key point for both understanding the disease pathology and developing treatments. We applied Maximum Relevance Minimum Redundancy (mRMR) algorithm to a set of microarray data generated from the CD4+ T cells of viremic non-progressors (VNPs) and rapid progressors (RPs) to identify host factors associated with the different responses to HIV infection. Using mRMR algorithm, 147 gene had been identified. Furthermore, we constructed a weighted molecular interaction network with the existing protein-protein interaction data from STRING database and identified 1331 genes on the shortest-paths among the genes identified with mRMR. Functional analysis shows that the functions relating to apoptosis play important roles during the pathogenesis of HIV infection. These results bring new insights of understanding HIV progression.
Liu, Lei
Exact and Approximate Truthful Mechanisms for the Shortest Paths Tree Problem
Let a communication network be modeled by an undirected graph G=(V,E) of n nodes and m edges, and assume that edges are controlled by selfish agents. In this paper we analyze the problem of designing a truthful\\u000a mechanism for computing one of the most popular structures in communication networks, i.e., the single-source shortest paths tree.\\u000a \\u000a \\u000a \\u000a More precisely, we will study
Luciano Gualŕ; Guido Proietti
Scaling of average weighted shortest path and average receiving time on weighted hierarchical networks
Recent work on the networks has focused on the weighted hierarchical networks that are significantly different from the un-weighted hierarchical networks. In this paper we study a family of weighted hierarchical networks which are recursively defined from an initial uncompleted graph, in which the weights of edges have been assigned to different values with certain scale. Firstly, we study analytically the average weighted shortest path (AWSP) on the weighted hierarchical networks. Using a recursive method, we determine explicitly the AWSP. The obtained rigorous solution shows that the networks grow unbounded but with the logarithm of the network size, while the weighted shortest paths stay bounded. Then, depending on a biased random walk, we research the mean first-passage time (MFPT) between a hub node and any peripheral node. Finally, we deduce the analytical expression of the average of MFPTs for a random walker originating from any node to first visit to a hub node, which is named as the average receiving time (ART). The obtained result shows that ART is bounded or grows sublinearly with the network order relating to the number of initial nodes and the weighted factor or grows quadratically with the iteration.
Sun, Yu; Dai, Meifeng; Xi, Lifeng
Fast Algorithms for Solving Path Problems
Let G = (V, E) be a directed graph with a distinguished source vertex s. The single-source path expression problem is to find, for each vertex v, a regular expression P(s, v) which represents the set of all paths in G from s to v A solution to this problem can be used to solve shortest path problems, solve sparse
Robert Endre Tarjan
Optimal Network Structure for Packet Flow in Shortest-Path Routing Control Model
A network structure is responsible for efficient communication through a computer network. In order to obtain a network structure suitable for optimal packet communication on the network, we introduce a cost function for the efficiency of packet communication. By means of numerical simulations, we find an optimized network structure by reconnecting links in the network so as to minimize the defined cost function by using a shortest-path routing control model for packet flow. It turns out that the obtained optimized networks have the small-world property but a different structure from Erdös and Rényi's random graph [P. Erdös and A. Rényi, Publ. Math. (Debrecen) 6 (1959), 290] nor the real Internet. In addition, the distribution of links in the obtained network is not homogeneous and hence different from that obtained by Guimerá} et al., who have also investigated an optimal network structure for packet communication without packet routing processes.
Yamaguchi, C.; Horiguchi, T.
The tomography of human mobility -- what do shortest-path trees reveal?
Similar to illustrating the anatomy of organs using pictures of tissue slices taken at various depths, we construct shortest-path trees of different nodes to create a tomogram of large-scale mobility networks. This tomography allows us to measure global properties of the system conditioned on a reference location in the network to gain a fuller characterization of a node. Using this technqiue, we discovered a new symmetry that characterizes a large class of mobility networks. Furthermore, introducing the notion of tree similarity, we devised a new technique for clustering nodes with similar topological footprint, yielding a new, unique and efficient method for community identification in these networks and extracting their topological backbone. We applied these methods to a multi-scale human mobility network obtained from the dollar-bill-tracking site wheresgoerge.com and to the U.S. and world-wide air transportation network.
Grady, Daniel; Thiemann, Christian; Brockmann, Dirk
Shortest path ray tracing in cell model with a second-level forward star
The high-level forward star is routinely applied in seismic ray tracing using graph theory (sometimes referred to as the shortest path method) with a grid model. For a cell model, the forward star is often restricted to nodes at the same cell (i.e. first-level forward star). The performance of a cell model with second-level forward stars is found to be comparable in both computation time and accuracy to that of a doubly dense cell model with first-level forward stars. Moreover, the cell model with second-level forward stars has the advantage of halving the required computer storage. An optimization of the secondary node geometry leads to a further 20 per cent improvement in accuracy. Concepts derived from grid models for analytical error estimation are found to be less applicable to cell models. An empirical approach works better in the optimization of the secondary node geometry.
Mak, Sum; Koketsu, Kazuki
Detection of Changes in Transitive Associations by Shortest-path Analysis of Protein Interaction Networks Integrated with Gene Expression Profiles
Shortest-path (SP) clustering can detect transitive associations in co-expression networks. In this work, we show that it can detect changes of transitive associations caused by perturbations in a protein interaction network (PIN). Specifically, we compare SPs between genes under perturbation and in a reference state. The PIN under perturbation can be obtained through integration with gene expression profiles, using either
Hong Qin; Li Yang
Identification of Colorectal Cancer Related Genes with mRMR and Shortest Path in Protein-Protein Interaction Network
One of the most important and challenging problems in biomedicine and genomics is how to identify the disease genes. In this study, we developed a computational method to identify colorectal cancer-related genes based on (i) the gene expression profiles, and (ii) the shortest path analysis of functional protein association networks. The former has been used to select differentially expressed genes
Bi-Qing Li; Tao Huang; Lei Liu; Yu-Dong Cai; Kuo-Chen Chou
We illustrate the use of the techniques of modern geometric optimal control theory by studying the shortest paths for a model of a car that can move forwards and backwards. This problem was discussed in recent work by Reeds and Shepp who showed, by special methods, (a) that shortest path motion could always be achieved by means of trajectories of
J. Sussmann; Guoqing Tang
Optimization of the measuring path on a coordinate measuring machine using genetic algorithms
Stamping dies, car bodies, turbine blades and other machine parts with curved surfaces are usually verified on coordinate measuring machines (CMMs). This is a time-consuming process with low productivity. This paper suggests genetic algorithms to optimize the measuring path on CMMs. The measuring head of a CMM can be considered as a traveling salesperson. To find the shortest measuring path
Liangsheng Qu; Guanhua Xu; Guohua Wang
Identification of Thyroid Carcinoma Related Genes with mRMR and Shortest Path Approaches.
Thyroid cancer is a malignant neoplasm originated from thyroid cells. It can be classified into papillary carcinomas (PTCs) and anaplastic carcinomas (ATCs). Although ATCs are in an very aggressive status and cause more death than PTCs, their difference is poorly understood at molecular level. In this study, we focus on the transcriptome difference among PTCs, ATCs and normal tissue from a published dataset including 45 normal tissues, 49 PTCs and 11 ATCs, by applying a machine learning method, maximum relevance minimum redundancy, and identified 9 genes (BCL2, MRPS31, ID4, RASAL2, DLG2, MY01B, ZBTB5, PRKCQ and PPP6C) and 1 miscRNA (miscellaneous RNA, LOC646736) as important candidates involved in the progression of thyroid cancer. We further identified the protein-protein interaction (PPI) sub network from the shortest paths among the 9 genes in a PPI network constructed based on STRING database. Our results may provide insights to the molecular mechanism of the progression of thyroid cancer. PMID:24718460
Xu, Yaping; Deng, Yue; Ji, Zhenhua; Liu, Haibin; Liu, Yueyang; Peng, Hu; Wu, Jian; Fan, Jingping
Challenging of path planning algorithms for autonomous robot in known environment
Most of the mobile robot path planning is estimated to reach its predetermined aim through the shortest path and avoiding the obstacles. This paper is a survey on path planning algorithms of various current research and existing system of Unmanned Ground Vehicles (UGV) where their challenging issues to be intelligent autonomous robot. The focuses are some short reviews on individual papers for UGV in the known environment. Methods and algorithms in path planning for the autonomous robot had been discussed. From the reviews, we obtained that the algorithms proposed are appropriate for some cases such as single or multiple obstacles, static or movement obstacle and optimal shortest path. This paper also describes some pros and cons for every reviewed paper toward algorithms improvement for further work.
Farah, R. N.; Irwan, N.; Zuraida, Raja Lailatul; Shaharum, Umairah; Hanafi@Omar, Hafiz Mohd
Analyzing the applicability of the least risk path algorithm in indoor space
Over the last couple of years, applications that support navigation and wayfinding in indoor environments have become one of the booming industries. However, the algorithmic support for indoor navigation has so far been left mostly untouched, as most applications mainly rely on adapting Dijkstra's shortest path algorithm to an indoor network. In outdoor space, several alternative algorithms have been proposed adding a more cognitive notion to the calculated paths and as such adhering to the natural wayfinding behavior (e.g. simplest paths, least risk paths). The need for indoor cognitive algorithms is highlighted by a more challenged navigation and orientation due to the specific indoor structure (e.g. fragmentation, less visibility, confined areas…). Therefore, the aim of this research is to extend those richer cognitive algorithms to three-dimensional indoor environments. More specifically for this paper, we will focus on the application of the least risk path algorithm of Grum (2005) to an indoor space. The algorithm as proposed by Grum (2005) is duplicated and tested in a complex multi-story building. Several analyses compare shortest and least risk paths in indoor and in outdoor space. The results of these analyses indicate that the current outdoor least risk path algorithm does not calculate less risky paths compared to its shortest paths. In some cases, worse routes have been suggested. Adjustments to the original algorithm are proposed to be more aligned to the specific structure of indoor environments. In a later stage, other cognitive algorithms will be implemented and tested in both an indoor and combined indoor-outdoor setting, in an effort to improve the overall user experience during navigation in indoor environments.
Vanclooster, A.; Viaene, P.; Van de Weghe, N.; Fack, V.; De Maeyer, Ph.
More Efficient Path-Finding Algorithm.
In this paper, we present a new routing algorithm, which we call path-finding algorithm (PFA). It drastically reduces the possibility of temporary routing loops, which accounts for its fast convergence properties. Like other path-finding algorithms, PFA o...
J. J. Garcia-Luna-Aceves S. Murthy
Performance Analysis of Reactive Shortest Single-path and Multipath Routing Mechanism With Load Balance
Research on multi-path routing protocols to provideimproved throughput and route resilience as compared withsingle-path routing has been explored in details in the contextof wired networks. However, multi-path routing mechanism hasnot been explored thoroughly in the domain of ad hoc networks.In this paper, we analyze and compare reactive single-path andmulti-path routing with load balance mechanisms in ad hoc networks,in terms of
Peter P. Pham; Sylvie Perreau
Adaptations of the A* algorithm for the computation of fastest paths in deterministic discrete-time dynamic networks
This paper extends the A* methodology to shortest path problems in dynamic networks, in which arc travel times are time dependent. We present efficient adaptations of the A* algorithm for computing fastest (minimum travel time) paths from one origin node to one destination node, for one as well as multiple departure times at the origin node, in a class of
Ismaďl Chabini; Shan Lan
Implementations of routing algorithms for transportation networks
We discuss the generalization of the point-to-point (and single-source) shortest path problem to instances where the shortest path must satisfy a formal language constraint. We describe theoretical and experimental results on a generalization of Dijkstra's algorithm to finding regular-language-constrained shortest paths. This algorithm forms a model for single-source shortest paths and point-to-point problems that generalizes several previously published algorithms for
Chris Barrett; Keith Bisset; Martin Holzer; Goran Konjevod; Madhav Marathe; Dorothea Wagnerk
Conflict-free shortest-time bidirectional AGV routeing
This paper presents an efficient algorithm for finding conflict-free shortest-time routes for automated guided vehicles moving in a bidirectional flow path network. The proposed algorithm is based on Dijkstra's shortest-path method. It maintains, for each node, a list of time windows reserved by scheduled vehicles and a list of free time windows available for vehicles to be scheduled. We introduce
A more efficient path-finding algorithm
Presents a new routing algorithm, which the authors call a path-finding algorithm (PFA). It drastically reduces the possibility of temporary routing loops, which accounts for its fast convergence properties. Like other path-finding algorithms, the PFA operates by specifying the second-to-last hop to each destination, in addition to the distance to the destination. A detailed proof of correctness and complexity is
Shree Murthy; J. J. Garcia-Luna-Aceves
A Multilevel Probabilistic Beam Search Algorithm for the Shortest Common Supersequence Problem
The shortest common supersequence problem is a classical problem with many applications in different fields such as planning, Artificial Intelligence and especially in Bioinformatics. Due to its NP-hardness, we can not expect to efficiently solve this problem using conventional exact techniques. This paper presents a heuristic to tackle this problem based on the use at different levels of a probabilistic variant of a classical heuristic known as Beam Search. The proposed algorithm is empirically analysed and compared to current approaches in the literature. Experiments show that it provides better quality solutions in a reasonable time for medium and large instances of the problem. For very large instances, our heuristic also provides better solutions, but required execution times may increase considerably.
Gallardo, Jose E.
A multilevel probabilistic beam search algorithm for the shortest common supersequence problem.
The shortest common supersequence problem is a classical problem with many applications in different fields such as planning, Artificial Intelligence and especially in Bioinformatics. Due to its NP-hardness, we can not expect to efficiently solve this problem using conventional exact techniques. This paper presents a heuristic to tackle this problem based on the use at different levels of a probabilistic variant of a classical heuristic known as Beam Search. The proposed algorithm is empirically analysed and compared to current approaches in the literature. Experiments show that it provides better quality solutions in a reasonable time for medium and large instances of the problem. For very large instances, our heuristic also provides better solutions, but required execution times may increase considerably. PMID:23300667
Gallardo, José E
Identification of colorectal cancer related genes with mRMR and shortest path in protein-protein interaction network.
One of the most important and challenging problems in biomedicine and genomics is how to identify the disease genes. In this study, we developed a computational method to identify colorectal cancer-related genes based on (i) the gene expression profiles, and (ii) the shortest path analysis of functional protein association networks. The former has been used to select differentially expressed genes as disease genes for quite a long time, while the latter has been widely used to study the mechanism of diseases. With the existing protein-protein interaction data from STRING (Search Tool for the Retrieval of Interacting Genes), a weighted functional protein association network was constructed. By means of the mRMR (Maximum Relevance Minimum Redundancy) approach, six genes were identified that can distinguish the colorectal tumors and normal adjacent colonic tissues from their gene expression profiles. Meanwhile, according to the shortest path approach, we further found an additional 35 genes, of which some have been reported to be relevant to colorectal cancer and some are very likely to be relevant to it. Interestingly, the genes we identified from both the gene expression profiles and the functional protein association network have more cancer genes than the genes identified from the gene expression profiles alone. Besides, these genes also had greater functional similarity with the reported colorectal cancer genes than the genes identified from the gene expression profiles alone. All these indicate that our method as presented in this paper is quite promising. The method may become a useful tool, or at least plays a complementary role to the existing method, for identifying colorectal cancer genes. It has not escaped our notice that the method can be applied to identify the genes of other diseases as well. PMID:22496748
Li, Bi-Qing; Huang, Tao; Liu, Lei; Cai, Yu-Dong; Chou, Kuo-Chen
Path Characterization Algorithms for FASCODE.
This report has described the results of a study undertaken at AER to identify and implement a state of the art nonlinear retrieval approach to characterize line of sight variability of atmospheric thermal and constituent environments. This path character...
B. L. Linder J. L. Moncet R. G. Isaacs S. A. Clough S. D. Worsham
Clustering incorporating shortest paths identifies relevant modules in functional interaction networks
Many biological systems can be modeled as networks. Hence, network analysis is of increasing importance to systems biology. We describe an evolutionary algorithm for selecting clusters of nodes within a large network based upon network topology together with a measure of the relevance of nodes to a set of independently identified genes of interest. We apply the algorithm to a
Jennifer Hallinan; Matthew R. Pocock; Stephen G. Addinall; David A. Lydall; Anil Wipat
UAV Path Planning Using Evolutionary Algorithms
Evolutionary Algorithms have been used as a viable candidate to solve path planning problems effectively and provide feasible\\u000a solutions within a short time. In this work a Radial Basis Functions Artificial Neural Network (RBF-ANN) assisted Differential\\u000a Evolution (DE) algorithm is used to design an off-line path planner for Unmanned Aerial Vehicles (UAVs) coordinated navigation\\u000a in known static maritime environments. A
Ioannis K. Nikolos; Eleftherios S. Zografos; Athina N. Brintaki
GPS-enabled mobiles for learning shortest paths: a pilot study
Recent GPS-enabled mobile phones provide a rich and novel platform for exploring new kinds of educational software. Moreover, powerful high-level programming languages such as Python allow rapid development of learning tools that take advantage of mobile technology. This paper reports on a recent pilot study using mobile phones as situated learning tools. The study focused on expressing Dijkstra's algorithm for
Jason J. Holdsworth; Siu Man Lui
Transmission Scheduling for Optimizing Sensor Network Lifetime: A Stochastic Shortest Path Approach
We present transmission scheduling algorithms for maximizing the lifetime of a sensor network. In each data collection, only one group of sensors are scheduled to transmit their measurements directly to an access point (AP) through a fading channel, causing a reduction in battery energy levels of these sensors. We formulate the problem of dynamically choosing which group of sensors should
Yunxia Chen; Qing Zhao; Vikram Krishnamurthy; Dejan V. Djonin
Identification of hepatocellular carcinoma related genes with k-th shortest paths in a protein-protein interaction network.
Hepatocellular carcinoma (HCC) is the most common type of liver cancer worldwide and one of the deadliest cancers in Asia. But at present, effective targets for HCC clinical therapy are still limited. The "guilt by association" rule suggests that interacting proteins share the same or similar functions and hence may be involved in the same pathway. This assumption can be used to identify disease related genes from protein association networks constructed from existing PPI data. Given the close association between Hepatitis B virus and Hepatitis B which may lead to HCC, here we develop a computational method to identify hepatocellular carcinoma related genes based on k-th shortest paths in the protein-protein interaction (PPI) network (we set k=1, 2 in this study). Finally, we found 33 genes whose p-values were less than 0.05, and most of them have been reported to be involved in HCC tumorigenesis and development. The results also provide a new reference for research into HCC oncogenesis and for development of new strategies for HCC clinical therapies. PMID:24056857
Jiang, Min; Chen, Yukang; Zhang, Yuchao; Chen, Lei; Zhang, Ning; Huang, Tao; Cai, Yu-Dong; Kong, XiangYin
Stochastic Evolutionary Algorithms for Planning Robot Paths
NASA Technical Reports Server (NTRS)
A computer program implements stochastic evolutionary algorithms for planning and optimizing collision-free paths for robots and their jointed limbs. Stochastic evolutionary algorithms can be made to produce acceptably close approximations to exact, optimal solutions for path-planning problems while often demanding much less computation than do exhaustive-search and deterministic inverse-kinematics algorithms that have been used previously for this purpose. Hence, the present software is better suited for application aboard robots having limited computing capabilities (see figure). The stochastic aspect lies in the use of simulated annealing to (1) prevent trapping of an optimization algorithm in local minima of an energy-like error measure by which the fitness of a trial solution is evaluated while (2) ensuring that the entire multidimensional configuration and parameter space of the path-planning problem is sampled efficiently with respect to both robot joint angles and computation time. Simulated annealing is an established technique for avoiding local minima in multidimensional optimization problems, but has not, until now, been applied to planning collision-free robot paths by use of low-power computers.
Fink, Wolfgang; Aghazarian, Hrand; Huntsberger, Terrance; Terrile, Richard
A Path Algorithm for Constrained Estimation
Many least-square problems involve affine equality and inequality constraints. Although there are a variety of methods for solving such problems, most statisticians find constrained estimation challenging. The current article proposes a new path-following algorithm for quadratic programming that replaces hard constraints by what are called exact penalties. Similar penalties arise in l1 regularization in model selection. In the regularization setting, penalties encapsulate prior knowledge, and penalized parameter estimates represent a trade-off between the observed data and the prior knowledge. Classical penalty methods of optimization, such as the quadratic penalty method, solve a sequence of unconstrained problems that put greater and greater stress on meeting the constraints. In the limit as the penalty constant tends to ?, one recovers the constrained solution. In the exact penalty method, squared penalties!are replaced by absolute value penalties, and the solution is recovered for a finite value of the penalty constant. The exact path-following method starts at the unconstrained solution and follows the solution path as the penalty constant increases. In the process, the solution path hits, slides along, and exits from the various constraints. Path following in Lasso penalized regression, in contrast, starts with a large value of the penalty constant and works its way downward. In both settings, inspection of the entire solution path is revealing. Just as with the Lasso and generalized Lasso, it is possible to plot the effective degrees of freedom along the solution path. For a strictly convex quadratic program, the exact penalty algorithm can be framed entirely in terms of the sweep operator of regression analysis. A few well-chosen examples illustrate the mechanics and potential of path following. This article has supplementary materials available online.
Zhou, Hua; Lange, Kenneth
Robot path planning using a genetic algorithm
Robot path planning can refer either to a mobile vehicle such as a Mars Rover, or to an end effector on an arm moving through a cluttered workspace. In both instances there may exist many solutions, some of which are better than others, either in terms of distance traversed, energy expended, or joint angle or reach capabilities. A path planning program has been developed based upon a genetic algorithm. This program assumes global knowledge of the terrain or workspace, and provides a family of good paths between the initial and final points. Initially, a set of valid random paths are constructed. Successive generations of valid paths are obtained using one of several possible reproduction strategies similar to those found in biological communities. A fitness function is defined to describe the goodness of the path, in this case including length, slope, and obstacle avoidance considerations. It was found that with some reproduction strategies, the average value of the fitness function improved for successive generations, and that by saving the best paths of each generation, one could quite rapidly obtain a collection of good candidate solutions.
Cleghorn, Timothy F.; Baffes, Paul T.; Wang, Liu
Adaptive path planning: Algorithm and analysis
To address the need for a fast path planner, we present a learning algorithm that improves path planning by using past experience to enhance future performance. The algorithm relies on an existing path planner to provide solutions difficult tasks. From these solutions, an evolving sparse work of useful robot configurations is learned to support faster planning. More generally, the algorithm provides a framework in which a slow but effective planner may be improved both cost-wise and capability-wise by a faster but less effective planner coupled with experience. We analyze algorithm by formalizing the concept of improvability and deriving conditions under which a planner can be improved within the framework. The analysis is based on two stochastic models, one pessimistic (on task complexity), the other randomized (on experience utility). Using these models, we derive quantitative bounds to predict the learning behavior. We use these estimation tools to characterize the situations in which the algorithm is useful and to provide bounds on the training time. In particular, we show how to predict the maximum achievable speedup. Additionally, our analysis techniques are elementary and should be useful for studying other types of probabilistic learning as well.
Chen, Pang C.
Path Computation Algorithms for Advanced Traveller Information System (ATIS)
Three path-planning algorithms for single-pair path computation are evaluated. These algorithms are the iterative breath-first search, Dijkstra's single-source path-planning algorithm, and the A* single-path planning algorithm. The performance of the algorithms is evaluated on graphs representing the roadmap of Minneapolis. In order to get an insight into their relative performance, synthetic grid maps are used as a benchmark computation. The
Shashi Shekhar; Ashim Kohli; Mark Coyle
An Implementation of Genetic Algorithm in Matlab: Solution to the Route Choice Problem in the Urban Traffic Network
Urban traffic network can be considered as an undirected graph. So the route choice problem in the traffic network can be converted to shortest path problem. The idea of using genetic algorithm to solve shortest path problem is proposed in this paper. The model of using genetic algorithm to solve shortest path problem which is programmed in Matlab is also
Jie Li; Minghao Zhu
The stable paths problem and interdomain routing
Dynamic routing protocols such as RIP and OSPF essentially implement distributed algorithms for solving the shortest paths problem. The border gateway protocol (BGP) is currently the only interdomain routing protocol deployed in the Internet. BGP does not solve a shortest paths problem since any interdomain protocol is required to allow policy-based metrics to override distance-based metrics and enable autonomous systems
Timothy G. Griffin; F. Bruce Shepherd; Gordon T. Wilfong
A Posture Scheduling Algorithm Using Constrained Shortest Path to Prevent Pressure Ulcers
Pressure ulcer is a severe threat for immobilized and peripheral neuropathic patients such as bed-ridden, elderly, and diabetics. Once developed, the complication of pressure ulcer causes pain, suffering, and longer hospitalization for the patients. Additionally, pressure ulcer management imposes a serious burden on the health care providers. The optimal strategy to deal with pressure ulcers is prevention. The current standard
S. Ostadabbas; R. Yousefi; M. Nourani; M. Faezipour; L. Tamil; M. Pompeo
Exact algorithms for the vehicle routing problem, based on spanning tree and shortest path relaxations
We consider the problem of routing vehicles stationed at a central facility (depot) to supply customers with known demands, in such a way as to minimize the total distance travelled. The problem is referred to as the vehicle routing problem (VRP) and is a generalization of the multiple travelling salesman problem that has many practical applications.
N. Christofides; A. Mingozzi; P. Toth
A Landmark Algorithm for the Time-Dependent Shortest Path Problem
Acknowledgments The author is heartily grateful to Professor Hiroshi Nagamochi for his continual guidance and invaluable suggestions to accomplish the thesis. He commented,in de- tail on the whole work in the thesis, which significantly improved the accuracy of the arguments and the quality of the expression. Without his generous help, none of this work could have been completed. He is
Hiroshi Nagamochi; Tatsuya Ohshima
Genetic regulatory networks established by shortest path algorithm and conditional probabilities for ovarian carcinoma microarray data
In the cancer research recently, it still doesn't have a definitive conclusion for the regulatory mechanisms of tumorigenesis and metastasis. But different genes have different biological functions, and these functions with interactions between genes play an important key in gene regulatory networks. Microarray is a tool most commonly used in the disease research, and scientists usually use that the feature
Meng-Hsiun Tsai; Hsiao-Han Ko; Sheng-Chuan Chiu
Real-time endovascular guidewire position simulation using shortest path algorithms
Purpose Treatment of vascular disease often involves endovascular interventions which use the vascular system for delivering treatment\\u000a devices via a previously inserted guidewire to the diseased site. Previous studies show relative reproducibility of guidewire\\u000a position after insertion, indicating that the guidewire position is constrained and could be represented by an energy minimization\\u000a approach. Such representation would support the surgeon's decision process
Sebastian Schafer; Vikas Singh; Peter B. Noël; Alan M. Walczak; Jinhui Xu; Kenneth R. Hoffmann
A Dynamic Shortest Path Algorithm Using Multi-Step Ahead Link Travel Time Prediction
Route guidance systems provide motorists with step-by-step instructions on how to get from any origin to any destination in a network. The systems calculate the best route from a user-supplied origin to destination, based on each link travel time on the network. Most studies on the route guidance development have been carried out based on only one-step ahead prediction of
Young-Ihn Lee; Seungjae Lee; Shinhae Lee; Jeunggyu Chon
A path-finding algorithm for loop-free routing
A loop-free path-finding algorithm (LPA) is presented;this is the first routing algorithm that eliminates theformation of temporary routing loops without the need forinternodal synchronization spanning multiple hops or thespecification of complete or variable-size path information.Like other previous algorithms, LPA operates by specifyingthe second-to-last hop and distance to each destination;this feature is used to ensure termination. In addition, LPAuses an inter-neighbor...
J. J. Garcia-Luna-Aceves; Shree Murthy
PCB Drill Path Optimization by Combinatorial Cuckoo Search Algorithm.
Optimization of drill path can lead to significant reduction in machining time which directly improves productivity of manufacturing systems. In a batch production of a large number of items to be drilled such as printed circuit boards (PCB), the travel time of the drilling device is a significant portion of the overall manufacturing process. To increase PCB manufacturing productivity and to reduce production costs, a good option is to minimize the drill path route using an optimization algorithm. This paper reports a combinatorial cuckoo search algorithm for solving drill path optimization problem. The performance of the proposed algorithm is tested and verified with three case studies from the literature. The computational experience conducted in this research indicates that the proposed algorithm is capable of efficiently finding the optimal path for PCB holes drilling process. PMID:24707198
Lim, Wei Chen Esmonde; Kanagaraj, G; Ponnambalam, S G
PCB Drill Path Optimization by Combinatorial Cuckoo Search Algorithm
Optimization of drill path can lead to significant reduction in machining time which directly improves productivity of manufacturing systems. In a batch production of a large number of items to be drilled such as printed circuit boards (PCB), the travel time of the drilling device is a significant portion of the overall manufacturing process. To increase PCB manufacturing productivity and to reduce production costs, a good option is to minimize the drill path route using an optimization algorithm. This paper reports a combinatorial cuckoo search algorithm for solving drill path optimization problem. The performance of the proposed algorithm is tested and verified with three case studies from the literature. The computational experience conducted in this research indicates that the proposed algorithm is capable of efficiently finding the optimal path for PCB holes drilling process.
Lim, Wei Chen Esmonde; Kanagaraj, G.; Ponnambalam, S. G.
Using interpolation to improve path planning: The Field D* algorithm
We present an interpolation-based planning and replanning algorithm for generating low-cost paths through uniform and nonuniform resolution grids. Most grid-based path planners use discrete state transitions that artificially constrain an agent's motion to a small set of possible headings e.g., 0, \\/4 , \\/2, etc.. As a result, even \\
Dave Ferguson; Anthony Stentz
Optimized Monte Carlo Path Generation using Genetic Algorithms
In this technical report we present a new method for optimizing the generation of paths in Monte Carlo global illumination rendering algorithms. Ray tracing, particle tracing, and bidirectional ray tracing all use random walks to estimate various fluxes in the scene. The probability density functions neces- sary to generate these random walks are optimized using a genetic algorithm, such that
F. Suykens; Y. D. Willems
Extracting contours of oval-shaped objects by Hough transform and minimal path algorithms
Circular and oval-like objects are very common in cell and micro biology. These objects need to be analyzed, and to that end, digitized images from the microscope are used so as to come to an automated analysis pipeline. It is essential to detect all the objects in an image as well as to extract the exact contour of each individual object. In this manner it becomes possible to perform measurements on these objects, i.e. shape and texture features. Our measurement objective is achieved by probing contour detection through dynamic programming. In this paper we describe a method that uses Hough transform and two minimal path algorithms to detect contours of (ovoid-like) objects. These algorithms are based on an existing grey-weighted distance transform and a new algorithm to extract the circular shortest path in an image. The methods are tested on an artificial dataset of a 1000 images, with an F1-score of 0.972. In a case study with yeast cells, contours from our methods were compared with another solution using Pratt's figure of merit. Results indicate that our methods were more precise based on a comparison with a ground-truth dataset. As far as yeast cells are concerned, the segmentation and measurement results enable, in future work, to retrieve information from different developmental stages of the cell using complex features.
Tleis, Mohamed; Verbeek, Fons J.
Identification of Influenza A/H7N9 Virus Infection-Related Human Genes Based on Shortest Paths in a Virus-Human Protein Interaction Network.
The recently emerging Influenza A/H7N9 virus is reported to be able to infect humans and cause mortality. However, viral and host factors associated with the infection are poorly understood. It is suggested by the "guilt by association" rule that interacting proteins share the same or similar functions and hence may be involved in the same pathway. In this study, we developed a computational method to identify Influenza A/H7N9 virus infection-related human genes based on this rule from the shortest paths in a virus-human protein interaction network. Finally, we screened out the most significant 20 human genes, which could be the potential infection related genes, providing guidelines for further experimental validation. Analysis of the 20 genes showed that they were enriched in protein binding, saccharide or polysaccharide metabolism related pathways and oxidative phosphorylation pathways. We also compared the results with those from human rhinovirus (HRV) and respiratory syncytial virus (RSV) by the same method. It was indicated that saccharide or polysaccharide metabolism related pathways might be especially associated with the H7N9 infection. These results could shed some light on the understanding of the virus infection mechanism, providing basis for future experimental biology studies and for the development of effective strategies for H7N9 clinical therapies. PMID:24955349
Zhang, Ning; Jiang, Min; Huang, Tao; Cai, Yu-Dong
Identification of Influenza A/H7N9 Virus Infection-Related Human Genes Based on Shortest Paths in a Virus-Human Protein Interaction Network
The recently emerging Influenza A/H7N9 virus is reported to be able to infect humans and cause mortality. However, viral and host factors associated with the infection are poorly understood. It is suggested by the "guilt by association" rule that interacting proteins share the same or similar functions and hence may be involved in the same pathway. In this study, we developed a computational method to identify Influenza A/H7N9 virus infection-related human genes based on this rule from the shortest paths in a virus-human protein interaction network. Finally, we screened out the most significant 20 human genes, which could be the potential infection related genes, providing guidelines for further experimental validation. Analysis of the 20 genes showed that they were enriched in protein binding, saccharide or polysaccharide metabolism related pathways and oxidative phosphorylation pathways. We also compared the results with those from human rhinovirus (HRV) and respiratory syncytial virus (RSV) by the same method. It was indicated that saccharide or polysaccharide metabolism related pathways might be especially associated with the H7N9 infection. These results could shed some light on the understanding of the virus infection mechanism, providing basis for future experimental biology studies and for the development of effective strategies for H7N9 clinical therapies.
Huang, Tao; Cai, Yu-Dong
Mobile transporter path planning using a genetic algorithm approach
The use of an optimization technique known as a genetic algorithm for solving the mobile transporter path planning problem is investigated. The mobile transporter is a traveling robotic vehicle proposed for the Space Station which must be able to reach any point of the structure autonomously. Specific elements of the genetic algorithm are explored in both a theoretical and experimental sense. Recent developments in genetic algorithm theory are shown to be particularly effective in a path planning problem domain, though problem areas can be cited which require more research. However, trajectory planning problems are common in space systems and the genetic algorithm provides an attractive alternative to the classical techniques used to solve these problems.
Baffes, Paul; Wang, Lui
Relativistic Path Integral as a Lattice-based Quantum Algorithm
We demonstrate the equivalence of two representations of many-body relativistic quantum mechanics: the quantum lattice-gas\\u000a method and the path integral method. The former serves as an efficient lattice-based quantum algorithm to simulate the space-time\\u000a dynamics of a system of Dirac particles.
Jeffrey Yepez
An Algorithm for Path Connections and Its Applications
The algorithm described in this paper is the outcome of an endeavor to answer the following question: Is it possible to find procedures which would enable a computer to solve efficiently path-connection problems inherent in logical drawing, wiring diagramming, and optimal route finding? The results are highly encouraging. Within our framework, we are able to solve the following types of
C. Y. Lee
Path Planning Algorithms for Autonomous Border Patrol Vehicles
This thesis presents an online path planning algorithm developed for unmanned vehicles in charge of autonomous border patrol. In this Pursuit-Evasion game, the unmanned vehicle is required to capture multiple trespassers on its own before any of them reach a target safe house where they are safe from capture. The problem formulation is based on Isaacs' Target Guarding problem, but extended to the case of multiple evaders. The proposed path planning method is based on Rapidly-exploring random trees (RRT) and is capable of producing trajectories within several seconds to capture 2 or 3 evaders. Simulations are carried out to demonstrate that the resulting trajectories approach the optimal solution produced by a nonlinear programming-based numerical optimal control solver. Experiments are also conducted on unmanned ground vehicles to show the feasibility of implementing the proposed online path planning algorithm on physical applications.
Lau, George Tin Lam
Using a modified invasive weed optimization algorithm for a personalized urban multi-criteria path optimization problem
The personalized urban multi-criteria quasi-optimum path problem (PUMQPP) is a branch of multi-criteria shortest path problems (MSPPs) and it is classified as a NP-hard problem. To solve the PUMQPP, by considering dependent criteria in route selection, there is a need for approaches that achieve the best compromise of possible solutions/routes. Recently, invasive weed optimization (IWO) algorithm is introduced and used as a novel algorithm to solve many continuous optimization problems. In this study, the modified algorithm of IWO was designed, implemented, evaluated, and compared with the genetic algorithm (GA) to solve the PUMQPP in a directed urban transportation network. In comparison with the GA, the results have shown the significant superiority of the proposed modified IWO algorithm in exploring a discrete search-space of the urban transportation network. In this regard, the proposed modified IWO algorithm has reached better results in fitness function, quality metric and running-time values in comparison with those of the GA.
Pahlavani, Parham; Delavar, Mahmoud R.; Frank, Andrew U.
A Bat Algorithm with Mutation for UCAV Path Planning
Path planning for uninhabited combat air vehicle (UCAV) is a complicated high dimension optimization problem, which mainly centralizes on optimizing the flight route considering the different kinds of constrains under complicated battle field environments. Original bat algorithm (BA) is used to solve the UCAV path planning problem. Furthermore, a new bat algorithm with mutation (BAM) is proposed to solve the UCAV path planning problem, and a modification is applied to mutate between bats during the process of the new solutions updating. Then, the UCAV can find the safe path by connecting the chosen nodes of the coordinates while avoiding the threat areas and costing minimum fuel. This new approach can accelerate the global convergence speed while preserving the strong robustness of the basic BA. The realization procedure for original BA and this improved metaheuristic approach BAM is also presented. To prove the performance of this proposed metaheuristic method, BAM is compared with BA and other population-based optimization methods, such as ACO, BBO, DE, ES, GA, PBIL, PSO, and SGA. The experiment shows that the proposed approach is more effective and feasible in UCAV path planning than the other models.
Wang, Gaige; Guo, Lihong; Duan, Hong; Liu, Luo; Wang, Heqi
Path planning algorithms for assembly sequence planning. [in robot kinematics
Planning for manipulation in complex environments often requires reasoning about the geometric and mechanical constraints which are posed by the task. In planning assembly operations, the automatic generation of operations sequences depends on the geometric feasibility of paths which permit parts to be joined into subassemblies. Feasible locations and collision-free paths must be present for part motions, robot and grasping motions, and fixtures. This paper describes an approach to reasoning about the feasibility of straight-line paths among three-dimensional polyhedral parts using an algebra of polyhedral cones. A second method recasts the feasibility conditions as constraints in a nonlinear optimization framework. Both algorithms have been implemented and results are presented.
Krishnan, S. S.; Sanderson, Arthur C.
The optimal path of logistics distribution in electronic commerce
Efficient and fast logistics distribution system is of paramount significance for enterprises, especially for the development of e-commerce. At present, the problem that e-commerce puzzles businessmen is logistics distribution. Based on Dijkstra's shortest path algorithm, an intelligent optimal path algorithm is presented with the aid of the thoughts of state space searching and dynamic cut branch in artificial intelligence. The
Zhang Yong-mei; Ma Li
Algorithm Plans Collision-Free Path for Robotic Manipulator
An algorithm has been developed to enable a computer aboard a robot to autonomously plan the path of the manipulator arm of the robot to avoid collisions between the arm and any obstacle, which could be another part of the robot or an external object in the vicinity of the robot. In simplified terms, the algorithm generates trial path segments and tests each segment for potential collisions in an iterative process that ends when a sequence of collision-free segments reaches from the starting point to the destination. The main advantage of this algorithm, relative to prior such algorithms, is computational efficiency: the algorithm is designed to make minimal demands upon the limited computational resources available aboard a robot. This path-planning algorithm utilizes a modified version of the collision-detection method described in "Improved Collision-Detection Method for Robotic Manipulator" (NPO-30356), NASA Tech Briefs, Vol. 27, No. 3 (June 2003), page 72. The method involves utilization of mathematical models of the robot constructed prior to operation and similar models of external objects constructed automatically from sensory data acquired during operation. This method incorporates a previously developed method, known in the art as the method of oriented bounding boxes (OBBs), in which an object is represented approximately, for computational purposes, by a box that encloses its outer boundary. Because many parts of a robotic manipulator are cylindrical, the OBB method has been extended in this method to enable the approximate representation of cylindrical parts by use of octagonal or other multiple-OBB assemblies denoted oriented bounding prisms (OBPs). A multiresolution OBB/OBP representation of the robot and its manipulator arm and a multiresolution OBB representation of external objects (including terrain) are constructed and used in a process in which collisions at successively finer resolutions are detected through computational detection of overlaps between the corresponding OBB and OBP models. For computational efficiency, the process is started at the coarsest resolution and stopped as soon as possible, preferably before reaching the finest resolution. At the coarsest resolution, there is a single OBB enclosing all relevant external objects and a single OBB enclosing the entire robot. At the next finer level of resolution, the coarsest-resolution OBB is divided into two OBBs, and so forth. If no collision is detected at the coarsest resolution, then there is no need for further computation to detect collisions. If a collision is detected at the coarsest resolution, then tests for collisions are performed at the next finer level of resolution. This process is continued to successively finer resolutions until either no more collisions are detected or the finest resolution is reached.
Backes, Paul; Diaz-Calderon, Antonio
A streamlined search algorithm for path modifications of a safe robot manipulator
In recent years, the interest in human-robot interactions has added a new dimension to the on-line path planning problem by\\u000a requiring a method that guarantees a risk-free path. This paper presents a streamlined search algorithm for fast path modification.\\u000a The algorithm is formulated as an optimization problem that evaluates alternative paths nearby each obstacle. Each path is\\u000a evaluated based on
Nima Najmaei; Mehrdad R. Kermani
Genetic Algorithm Based Path Planning and Optimization for Autonomous Mobile Robots with Morphological Preprocessing
This paper presents an algorithm for optimal path planning for mobile robots using genetic algorithms coupled with morphological image preprocessing of the terrain. Path planning in a given environment, being a NP-hard problem, is computationally demanding especially if exact or deterministic techniques are employed. This paves the way for the use of evolutionary computing techniques, such as genetic algorithms (GAs),
Fayyaz A. Afsar; M. Arif; M. Hussain
Evolutionary algorithm based offline\\/online path planner for UAV navigation
Abstract—An evolutionary algorithm based framework, a combination of modified breeder genetic algorithms incorporating characteristics of classic genetic algorithms, is utilized to design an offline\\/online path planner for unmanned,aerial vehicles (UAVs) autonomous,navigation. The path planner calculates a curved path line with desired characteristics in a three?dimensional (3-D) rough terrain environment, represented using B-Spline curves, with the coordinates of its control points
Ioannis K. Nikolos; Kimon P. Valavanis; Nikos C. Tsourveloudis; Anargyros N. Kostaras
Real time path-planning algorithm and guidance law for the glider bomb
This paper describes a real time path-planning algorithm and guidance law for the glider bomb to increase its launching range (shooting range). To maximize the launching range of the glider bomb, the flight path angle is maintained a certain value, it is called the optimal flight path angle, which is determined by aerodynamic characteristic of the bomb and external wind
Chang-Hun Lee; Tae-Hun Kim; Min-Jea Tahk
Mobile robot path planning based on shuffled frog leaping optimization algorithm
Mobile robot path planning is a nondeterministic polynomial time (NP) problem, traditional optimization methods are not very effective to it, which are easy to plunge into local minimum. In this paper, we devise an evolutionary algorithm to solve the robot path planning problem. In the present work, we propose a method of robot path planning in partially unknown environments based
I. Hassanzadeh; K. Madani; M. A. Badamchizadeh
A Dynamic Critical Path Algorithm for Scheduling Scientific Workflow Applications on Global Grids
Effective scheduling is a key concern for the execution of performance driven Grid applications. In this paper, we propose a Dynamic Critical Path (DCP) based workflow scheduling algorithm that determines effi- cient mapping of tasks by calculating the critical path in the workflow task graph at every step. It assigns priority to a task in the critical path which is
Mustafizur Rahman; Srikumar Venugopal; Rajkumar Buyya
A Log(N) Distributed Mutual Exclusion Algorithm Based on Path Reversal
In this paper, we present a distributed algorithm for mutual exclusion based on path reversal. The algorithm does not use logical clocks to serialize the concurrent events, and all the variables are bounded. When a process invokes a critical section, it sends a request to the tail of a queue. A dynamical rooted tree gives the path to this tail.
Mohamed Naimi; Michel Trehel; André Arnold
Selection of optimal emergency rescue route based on improved ant colony algorithm
The optimal path problem has always been the research core of city emergency rescue. Its research goal has developed from looking for "the shortest path" to searching "the optimal path". The related algorithms differ in different circumstances. In addition to distance problem, the influence of various practical factors should also be considered under the complicated actual conditions. An improved algorithm
Baojie Li; Hehe Gu; Yazhou Ji
Automatic path-planning algorithm maximizing observation area for virtual colonoscopy
To navigate a colon lumen, a proper camera path should be generated prior to the navigation. Conventional path-planning algorithms try to find an accurate and robust centerline by assuming that a centerline of colon lumen is the best choice for camera path. For efficient and reliable navigation, however, the centerline may not minimize unobservable area from the camera path. In this paper, we first define a new coverage measure reflecting the temporal visibility. And based on this measure, a fast and efficient path-planning algorithm is proposed to increase the visibility coverage. The proposed algorithm first simplifies the object surface using the centerline determined. Then, camera view positions and directions are estimated to maximize the observable surface. Simulation results prove that the proposed algorithm provides a better coverage rate than the conventional one without a significant increase of additional computation.
Kang, Dong-Goo; Ra, Jong Beom
For least squares regression, Efron et al. (2004) proposed an efficient solution path algorithm, the least angle regression (LAR). They showed that a slight modification of the LAR leads to the whole LASSO solution path. Both the LAR and LASSO solution paths are piecewise linear. Recently Wu (2011) extended the LAR to generalized linear models and the quasi-likelihood method. In this work we extend the LAR further to handle Cox's proportional hazards model. The goal is to develop a solution path algorithm for the elastic net penalty (Zou and Hastie (2005)) in Cox's proportional hazards model. This goal is achieved in two steps. First we extend the LAR to optimizing the log partial likelihood plus a fixed small ridge term. Then we define a path modification, which leads to the solution path of the elastic net regularized log partial likelihood. Our solution path is exact and piecewise determined by ordinary differential equation systems.
Wu, Yichao
New heuristic algorithms for efficient hierarchical path planning
The authors consider one of the most popular approaches to path planning: hierarchical approximate cell decomposition. This approach consists of constructing successive decompositions of the robot's configuration space into rectangloid cells and searching the connectivity graph built at each level of decomposition for a path. Despite its conceptual simplicity, an efficient implementation of this approach raises many delicate questions that
David Zhu; Jean-Claude Latombe
Approximating Disjoint-Path Problems Using Greedy Algorithms and Packing Integer Programs
The edge and vertex-disjoint path problems together with their unsplittable flow generalization are NP-hard problems with a multi- tude of applications in areas such as routing, scheduling and bin packing. Given the hardness of the problems, we study polynomial-time approxi- mation algorithms with bounded performance guarantees. We introduce techniques which yield new algorithms for a wide range of disjoint-path problems.
Stavros G. Kolliopoulos; Clifford Stein
A New Algorithm for Robot Path Planning Based on Scout Ant Cooperation
A new ant algorithm for robot path planning is presented according to the latest achievements of research on actual ants. In this algorithm, m scout ants collaborate with each other to search for an optimal or near-optimal path. Of m scout ants, n ants adopt nearest-neighbor search strategy and the left q=m-n ants adopt random search strategy. A section of
Qingbao Zhu; Lingling Wang
Automatic Path-Oriented Test Data Generation Using a Multi-population Genetic Algorithm
Automatic path-oriented test data generation is an undecidable problem and genetic algorithm (GA) has been used to test data generation since 1992. In favor of MATLAB, a multi-population genetic algorithm (MPGA) was implemented, which selects individuals for free migration based on their fitness values. Applying MPGA to generating path-oriented test data generation is a new and meaningful attempt. After depicting
Yong Chen; Yong Zhong
Improved Algorithms for the 2Vertex Disjoint Paths Problem
Given distinct vertices s\\u000a 1,s\\u000a 2,t\\u000a 1, and t\\u000a 2 the 2-vertex-disjoint paths problem (2-VDPP) consists in determining two vertex-disjoint paths p\\u000a 1, from s\\u000a 1 to t\\u000a 1, and p\\u000a 2, from s\\u000a 2 to t\\u000a 2, if such paths exist.\\u000a \\u000a We show that by using some kind of sparsification technique the previously best known time bound of O(n?+?m?(m,n))
Torsten Tholey
Optimal Algorithm for Shape from Shading and Path Planning
. An optimal algorithm for the reconstruction of a surface from its shadingimage is presented. The algorithm solves the 3D reconstruction from a single shadingimage problem. The shading image is treated as a penalty function and the heightof the reconstructed surface is a weighted distance. A consistent numerical schemebased on Sethian's fast marching method is used to compute the reconstructedsurface.
Ron Kimmel; James A. Sethian
An Algorithm for the Hierarchical Organization of Path Diagrams and Calculation of Components of Expected Covariance.
Presents an algorithm for the production of a graphical diagram from a matrix formula in such a way that its components are logically and hierarchically arranged. The algorithm, which relies on the matrix equations of J. McArdle and R. McDonald (1984), calculates the individual path components of expected covariance between variables and…
Boker, Steven M.; McArdle, J. J.; Neale, Michael
Path planning using a hybrid evolutionary algorithm based on tree structure encoding.
A hybrid evolutionary algorithm using scalable encoding method for path planning is proposed in this paper. The scalable representation is based on binary tree structure encoding. To solve the problem of hybrid genetic algorithm and particle swarm optimization, the "dummy node" is added into the binary trees to deal with the different lengths of representations. The experimental results show that the proposed hybrid method demonstrates using fewer turning points than traditional evolutionary algorithms to generate shorter collision-free paths for mobile robot navigation. PMID:24971389
Ju, Ming-Yi; Wang, Siao-En; Guo, Jian-Horn
Path Planning Using a Hybrid Evolutionary Algorithm Based on Tree Structure Encoding
A hybrid evolutionary algorithm using scalable encoding method for path planning is proposed in this paper. The scalable representation is based on binary tree structure encoding. To solve the problem of hybrid genetic algorithm and particle swarm optimization, the "dummy node" is added into the binary trees to deal with the different lengths of representations. The experimental results show that the proposed hybrid method demonstrates using fewer turning points than traditional evolutionary algorithms to generate shorter collision-free paths for mobile robot navigation.
Wang, Siao-En; Guo, Jian-Horn
Robust Flight Path Determination for Mars Precision Landing Using Genetic Algorithms
This paper documents the application of genetic algorithms (GAs) to the problem of robust flight path determination for Mars precision landing. The robust flight path problem is defined here as the determination of the flight path which delivers a low-lift open-loop controlled vehicle to its desired final landing location while minimizing the effect of perturbations due to uncertainty in the atmospheric model and entry conditions. The genetic algorithm was capable of finding solutions which reduced the landing error from 111 km RMS radial (open-loop optimal) to 43 km RMS radial (optimized with respect to perturbations) using 200 hours of computation on an Ultra-SPARC workstation. Further reduction in the landing error is possible by going to closed-loop control which can utilize the GA optimized paths as nominal trajectories for linearization.
Bayard, David S.; Kohen, Hamid
Limited path percolation in complex networks.
We study the stability of network communication after removal of a fraction q=1-p of links under the assumption that communication is effective only if the shortest path between nodes i and j after removal is shorter than al(ij)(a> or =1) where l(ij) is the shortest path before removal. For a large class of networks, we find analytically and numerically a new percolation transition at p(c)=(kappa(0)-1)((1-a)/a), where kappa(0) [triple bond] / and k is the node degree. Above p(c), order N nodes can communicate within the limited path length al(ij), while below p(c), N(delta) (delta<1) nodes can communicate. We expect our results to influence network design, routing algorithms, and immunization strategies, where short paths are most relevant. PMID:17995444
López, Eduardo; Parshani, Roni; Cohen, Reuven; Carmi, Shai; Havlin, Shlomo
A Hybrid Metaheuristic DE/CS Algorithm for UCAV Three-Dimension Path Planning
Three-dimension path planning for uninhabited combat air vehicle (UCAV) is a complicated high-dimension optimization problem, which primarily centralizes on optimizing the flight route considering the different kinds of constrains under complicated battle field environments. A new hybrid metaheuristic differential evolution (DE) and cuckoo search (CS) algorithm is proposed to solve the UCAV three-dimension path planning problem. DE is applied to optimize the process of selecting cuckoos of the improved CS model during the process of cuckoo updating in nest. The cuckoos can act as an agent in searching the optimal UCAV path. And then, the UCAV can find the safe path by connecting the chosen nodes of the coordinates while avoiding the threat areas and costing minimum fuel. This new approach can accelerate the global convergence speed while preserving the strong robustness of the basic CS. The realization procedure for this hybrid metaheuristic approach DE/CS is also presented. In order to make the optimized UCAV path more feasible, the B-Spline curve is adopted for smoothing the path. To prove the performance of this proposed hybrid metaheuristic method, it is compared with basic CS algorithm. The experiment shows that the proposed approach is more effective and feasible in UCAV three-dimension path planning than the basic CS model.
Wang, Gaige; Guo, Lihong; Duan, Hong; Wang, Heqi; Liu, Luo; Shao, Mingzhen
We investigate the performance of a a constrained optimisation Genetic Algorithm (GA) for solving the Bandwidth Allocation for Virtual Paths (BAVP) problem, and compare it with a classical constrained optimisation (CCO) algorithm. We compare throughput, fairness and time complexity of GA-BAVP and CCO-BAVP for several node topologies. The results on maximising the throughput obtained with GA-BAVP and CCO- BAVP are
C. S. Pattichis; A. Pitsillides; G. Stylianou; A. Sekercioglu; A. Vasilakos
A Loop-Free Path-Finding Algorithm: Specification, Verification and Complexity
The loop-free path-finding algorithm (LPA) is presented.LPA specifies the second-to-last hop and distanceto each destination to ensure termination; in addition,it uses an inter-neighbor synchronization mechanismto eliminate temporary loops. A detailed proofof LPA's correctness is presented and its complexity isevaluated. LPA's average performance is compared bysimulation with the performance of algorithms representativeof the state of the art in distributed routing,namely an
J. J. Garcia-luna-aceves; Shree Murthy
Pareto memetic algorithm with path relinking for bi-objective traveling salesperson problem
The paper presents an effective version of the Pareto memetic algorithm with path relinking and efficient local search for multiple objective traveling salesperson problem. In multiple objective Traveling salesperson problem (TSP), multiple costs are associated with each arc (link). The multiple costs may for example correspond to the financial cost of travel along a link, time of travel, or risk
Andrzej Jaszkiewicz; Piotr Zielniewicz
Flight path reconstruction – A comparison of nonlinear Kalman filter and smoother algorithms
This paper is concerned with the choice of a state-estimation algorithm to perform the flight path reconstruction (FPR) procedure. Both simulated data and experimental data collected from a sailplane aircraft are used to illustrate the methods investigated. In both cases the unscented Kalman filter (UKF) is employed to determine the biases associated to each accelerometer and gyro in the inertial
Bruno O. S. Teixeira; Leonardo A. B. Tôrres; Paulo Iscold; Luis A. Aguirre
An evolution based path planning algorithm for autonomous motion of a UAV through uncertain environments
Adaptive and intelligent on-board path planning is a required part of a fully autonomous UAV. In controlled airspace, such a UAV would have to interact with other vehicles moving though its environment. The locations of obstacles (other vehicles) that form obstructions in the environment may only be known with limited accuracy. Evolutionary algorithms (EA) have been successfully used to compute
David Rathbun; Sean Kragelund; Anawat Pongpunwattana; Brian Capozzi
Evolutionary algorithm based offline/online path planner for UAV navigation.
An evolutionary algorithm based framework, a combination of modified breeder genetic algorithms incorporating characteristics of classic genetic algorithms, is utilized to design an offline/online path planner for unmanned aerial vehicles (UAVs) autonomous navigation. The path planner calculates a curved path line with desired characteristics in a three-dimensional (3-D) rough terrain environment, represented using B-spline curves, with the coordinates of its control points being the evolutionary algorithm artificial chromosome genes. Given a 3-D rough environment and assuming flight envelope restrictions, two problems are solved: i) UAV navigation using an offline planner in a known environment, and, ii) UAV navigation using an online planner in a completely unknown environment. The offline planner produces a single B-Spline curve that connects the starting and target points with a predefined initial direction. The online planner, based on the offline one, is given on-board radar readings which gradually produces a smooth 3-D trajectory aiming at reaching a predetermined target in an unknown environment; the produced trajectory consists of smaller B-spline curves smoothly connected with each other. Both planners have been tested under different scenarios, and they have been proven effective in guiding an UAV to its final destination, providing near-optimal curved paths quickly and efficiently. PMID:18238242
Nikolos, I K; Valavanis, K P; Tsourveloudis, N C; Kostaras, A N
A Monte-Carlo algorithm for path planning with many degrees of freedom
A stochastic technique is described for planning collision-free paths of robots with many degrees of freedom (DOFs). The algorithm incrementally builds a graph connecting the local minima of a potential function defined in the robot's configuration space and concurrently searches the graph until a goal configuration is attained. A local minimum is connected to another one by executing a random
J. Barraquand; J.-C. Latombe
Generalized Hough transform: A useful algorithm for signal path detection
How is it possible to recognize ETI signals coming from exoplanets? This is one of the questions that SETI researchers must answer. In early 1998, the Italian SETI program [S. Montebugnoli, et al., SETItalia, A new era in bioastronomy, ASP Conference Series, vol. 213, 2000, pp. 501-504.] started in Medicina with the installation of the Serendip IV 24Million Channel digital spectrometer. This system daily acquires a huge quantity of data to be processed off line, in order to detect possible ETI signals. The programs devoted to this topic are collectively called SALVE 2. Here a natural evolution of a previous effort is presented, which was based on a simple Hough transform and was limited to the detection of short linear tracks in the join time frequency matrix (JTFM) stored by SIV. The new generalized Hough algorithm allows us to detect the sinusoidal tracks by the transformation of the JTF bidimensional Cartesian space (x,y), in the generalized Hough quadridimensional space, where the main vectors are the sine parameters amplitude, frequency, phase and offset. At the end of the paper some results, obtained with the computation of real and simulated JTFM, are shown.
Monari, Jader; Montebugnoli, Stelio; Orlati, Andrea; Ferri, Massimo; Leone, Giorgio
Retrievals of XCH4 from GOSAT: comparison between full physics and light path proxy algorithms
The Greenhouse gas Observing Satellite (GOSAT), launched in 2009, measures near-infrared spectra of sunlight backscattered by the Earth's surface and atmosphere. These spectra show absorption features of CO2 and CH4 that allow for retrieval of their concentration with high sensitivity in the lower atmosphere. However, a major source of uncertainty in these retrievals is the unknown light path modification introduced through scattering by aerosol and cirrus particles in the Earth's atmosphere. We have compared two algorithms for retrieving the column-average dry air mole fraction of methane (XCH4) based on two distinctly different ways of dealing with the unknown light path modification. On the one hand, we developed a 'full physics' algorithm (Butz et al. 2009, 2011), where scattering effects are parametrized by three effective parameters representing aerosol size, amount and height distribution. On the other hand, the 'proxy' algorithm developed by Frankenberg et al. (2005) uses simultaneously retrieved CO2 as a proxy for light path. We have applied both methods to retrieve XCH4 using the first year of GOSAT-FTS observations and validated the retrieved XCH4 against collocated ground-based observations from the Total Carbon Column Observing Network (TCCON). We find that both algorithms show comparably good performance with XCH4 residuals in the sub-percent at TCCON sites across the globe. Furthermore we compare global methane field retrieved with our algorithms to TM5 model fields.
Schepers, D.; Guerlet, S.; Butz, A.; Hasekamp, O. P.; Aben, I.
Optimal Path Planning Program for Autonomous Speed Sprayer in Orchard Using Order-Picking Algorithm
This study was conducted to develop a software program which computes optimal path for autonomous navigation in orchard, especially for speed sprayer. Possibilities of autonomous navigation in orchard were shown by other researches which have minimized distance error between planned path and performed path. But, research of planning an optimal path for speed sprayer in orchard is hardly founded. In this study, a digital map and a database for orchard which contains GPS coordinate information (coordinates of trees and boundary of orchard) and entity information (heights and widths of trees, radius of main stem of trees, disease of trees) was designed. An orderpicking algorithm which has been used for management of warehouse was used to calculate optimum path based on the digital map. Database for digital map was created by using Microsoft Access and graphic interface for database was made by using Microsoft Visual C++ 6.0. It was possible to search and display information about boundary of an orchard, locations of trees, daily plan for scattering chemicals and plan optimal path on different orchard based on digital map, on each circumstance (starting speed sprayer in different location, scattering chemicals for only selected trees).
Park, T. S.; Park, S. J.; Hwang, K. Y.; Cho, S. I.
What Structural Features Make Graph Problems to Have Efficient Parallel Algorithms? —Using Outerplanar Graphs, Trapezoid Graphs and In-Tournament Graphs as Examples
SUMMARY This paper analyzes what structural features of graph problems allow efficient parallel algorithms. We survey some parallel algorithms for typical problems on three kinds of graphs, outerplanar graphs, trapezoid graphs and in-tournament graphs. Our results on the shortest path problem, the longest path problem and the maximum flow problem on outerplanar graphs, the minimum-weight connected dominating set problem and
Shigeru MASUYAMA; Shin-ichi NAKAYAMA
Calibration of neural networks using genetic algorithms, with application to optimal path planning
Genetic algorithms (GA) are used to search the synaptic weight space of artificial neural systems (ANS) for weight vectors that optimize some network performance function. GAs do not suffer from some of the architectural constraints involved with other techniques and it is straightforward to incorporate terms into the performance function concerning the metastructure of the ANS. Hence GAs offer a remarkably general approach to calibrating ANS. GAs are applied to the problem of calibrating an ANS that finds optimal paths over a given surface. This problem involves training an ANS on a relatively small set of paths and then examining whether the calibrated ANS is able to find good paths between arbitrary start and end points on the surface.
Smith, Terence R.; Pitney, Gilbert A.; Greenwood, Daniel
NSDL National Science Digital Library
Started in the 1970s as an agency to assist men and women in gaining access to a variety of birth control methods, PATH has since expanded its focus to provide "sustainable, culturally relevant [health] solutions, enabling communities worldwide to break longstanding cycles of poor health." The PATH website has more than a dozen videos and slideshows available to visitors at the "Our Multimedia" link near the bottom right hand corner of the homepage. A three-minute video entitled "Better Nutrition For Life" educates visitors about an innovative rice product that could bring greater nutrition to millions of malnourished people where rice is a staple food. The product is Ultra Rice, and is actually fortified pasta that looks, cooks, and tastes like rice, but is fortified with nutrients. The "rice" can be fortified with the needed nutrients the particular population being served is lacking. A slideshow about TB in the Ukraine, explains to visitors why there has been a resurgence of TB in Eastern Europe, and how PATH and its partners set out to help control it throughout the region.
Worm Algorithm for Continuous-Space Path Integral Monte Carlo Simulations
We present a new approach to path integral Monte Carlo (PIMC) simulations based on the worm algorithm, originally developed for lattice models and extended here to continuous-space many-body systems. The scheme allows for efficient computation of thermodynamic properties, including winding numbers and off-diagonal correlations, for systems of much greater size than that accessible to conventional PIMC simulations. As an illustrative application of the method, we simulate the superfluid transition of {sup 4}He in two dimensions.
Boninsegni, Massimo [Department of Physics, University of Alberta, Edmonton, Alberta T6G 2J1 (Canada); Prokof'ev, Nikolay [Department of Physics, University of Alberta, Edmonton, Alberta T6G 2J1 (Canada); Department of Physics, University of Massachusetts, Amherst, Massachusetts 01003 (United States); Russian Research Center 'Kurchatov Institute', 123182 Moscow (Russian Federation); Department of Physics, Cornell University, Ithaca, New York 14850 (United States); Svistunov, Boris [Department of Physics, University of Massachusetts, Amherst, Massachusetts 01003 (United States); Russian Research Center 'Kurchatov Institute', 123182 Moscow (Russian Federation)
Optimizing Graph Algorithms for Improved Cache Performance
We develop algorithmic optimizations to improve the cache performance of four fundamental graph algorithms. We present a cache-oblivious implementation of the Floyd-Warshall algorithm for the fundamental graph problem of all-pairs shortest paths by relaxing some dependencies in the iterative version. We show that this implementation achieves the lower bound on processor-memory traffic of ?(N3\\/?C), where N and C are the
Joon-sang Park; Michael Penner; Viktor K. Prasanna
Application of GA, PSO, and ACO algorithms to path planning of autonomous underwater vehicles
In this paper, an underwater vehicle was modeled with six dimensional nonlinear equations of motion, controlled by DC motors in all degrees of freedom. Near-optimal trajectories in an energetic environment for underwater vehicles were computed using a numerical solution of a nonlinear optimal control problem (NOCP). An energy performance index as a cost function, which should be minimized, was defined. The resulting problem was a two-point boundary value problem (TPBVP). A genetic algorithm (GA), particle swarm optimization (PSO), and ant colony optimization (ACO) algorithms were applied to solve the resulting TPBVP. Applying an Euler-Lagrange equation to the NOCP, a conjugate gradient penalty method was also adopted to solve the TPBVP. The problem of energetic environments, involving some energy sources, was discussed. Some near-optimal paths were found using a GA, PSO, and ACO algorithms. Finally, the problem of collision avoidance in an energetic environment was also taken into account.
Aghababa, Mohammad Pourmahmood; Amrollahi, Mohammad Hossein; Borjkhani, Mehdi
Formulation of Quantum Statistical Mechanics Based on the Feynman Path Centroid Density IV. Algorithms for Centroid Molecular Dynamics.
Numerical algorithms are developed for the centroid molecular dynamics (centroid MD) method to calculate dynamical time correlation functions for general many-body quantum systems. Approaches based on the normal mode path integral molecular dynamics and s...
J. Cao G. A. Voth
A novel shared-path protection algorithm with correlated risk against multiple failures in flexible bandwidth optical networks
In this paper, to decrease the traffic loss caused by multiple link failures, we consider the correlated risk among different connection requests when both the primary and backup paths are routed and assigned spectrum. Therefore, a novel shared-path protection algorithm is developed, named shared-path protection algorithm with correlated risk (SPP_CR), in flexible bandwidth optical networks. Based on the correlated risk, the routing can be diverse and the sharing in backup spectral resource will be restricted by SPP_CR algorithm, then the dropped traffic caused by simultaneous multiple failures between primary and backup path can be efficiently decreased. Simulation results show that, SPP_CR algorithm (i) achieves the higher successful service ratio (SSR) than traditional shared-path protection (SPP), shared-path protection with dynamic load balancing (SPP_DLB) and dedicated path protection (DPP); (ii) makes a better tradeoff in blocking probability, protection ratio (PR), average frequency slots consumed (AFSC) and redundancy ratio (RR) than SPP, SPP_DLB and DPP algorithms.
Zhang, Jie; Lv, Chunhui; Zhao, Yongli; Chen, Bowen; Li, Xin; Huang, Shanguo; Gu, Wanyi
Reaction path study of helix formation in tetrapeptides: Effect of side chains
A computational protocol to calculate steepest descent paths in flexible molecules is discussed in detail. The algorithm does not use second derivatives and related matrices, and is therefore suitable for large systems. The shortest reaction coordinate from the helix to the extended chain conformation is calculated for a series of different tetrapeptides. The formation of a helical turn is investigated
Chyung Choi; Ron Elber
Rotational fluctuation of molecules in quantum clusters. I. Path integral hybrid Monte Carlo algorithm
In this paper, we present a path integral hybrid Monte Carlo (PIHMC) method for rotating molecules in quantum fluids. This is an extension of our PIHMC for correlated Bose fluids [S. Miura and J. Tanaka, J. Chem. Phys. 120, 2160 (2004)] to handle the molecular rotation quantum mechanically. A novel technique referred to be an effective potential of quantum rotation is introduced to incorporate the rotational degree of freedom in the path integral molecular dynamics or hybrid Monte Carlo algorithm. For a permutation move to satisfy Bose statistics, we devise a multilevel Metropolis method combined with a configurational-bias technique for efficiently sampling the permutation and the associated atomic coordinates. Then, we have applied the PIHMC to a helium-4 cluster doped with a carbonyl sulfide molecule. The effects of the quantum rotation on the solvation structure and energetics were examined. Translational and rotational fluctuations of the dopant in the superfluid cluster were also analyzed.
Miura, Shinichi [Institute for Molecular Science, 38 Myodaiji, Okazaki 444-8585 (Japan)
Optimal robust path planning in general environments
The authors address robust path planning for a mobile agent in a general environment by finding minimum cost source-destination paths having prescribed widths. The main result is a new approach that optimally solves the robust path planning problem using an efficient network flow formulation. Their algorithm represents a significant departure from conventional shortest-path or graph search based methods; it not only handles environments with solid polygonal obstacles, but also generalizes to arbitrary cost maps that may arise in modeling incomplete or uncertain knowledge of the environment. Simple extensions allow them to address higher dimensional problems instances and minimum-surface computations; the latter is a result of independent interest. They use an efficient implementation to exhibit optimal path-planning solutions for a variety of test problems. The paper concludes with open issues and directions for future work.
Hu, T.C. (Univ. of California, San Diego, La Jolla, CA (United States). Computer Science and Engineering Dept.); Kahng, A.B. (Univ. of California, Los Angeles, CA (United States). Computer Science Dept.); Robins, G. (Univ. of Virginia, Charlottesville, VA (United States). Dept. of Computer Science)
Faster and Simpler Algorithms for Multicommodity Flow and Other Fractional Packing Problems
This paper considers the problem of designing fast, approx- imate, combinatorial algorithms for multicommodity flows and other fractional packing problems. We provide a dif- ferent approach to these problems which yields faster and much simpler algorithms. Our approach also allows us to substitute shortest path computations for min-cost flow computations in computing maximum concurrent flow and min-cost multicommodity flow; this
Naveen Garg; Jochen Könemann
An Energy-Ecien t Scatternet Formation Algorithm for Bluetooth-Based Sensor Networks
In this paper, we propose an energy-ecient scatternet formation algorithm for Bluetooth based sensor networks. The algorithm is based on rst computing a shortest path tree from the base sta- tion to all sensor nodes and then solving the de- gree constraint problem so that the degree of each node in the network is not greater than seven, which is
Sain Saginbekov; Ibrahim Korpeoglu
A Hybrid Approach of Path Planning for Mobile Robots Based on the Combination of ACO and APF Algorithms
This paper presents an optimal method based on combination of artificial potential field (APF) and ant colony optimization (ACO) algorithms for global path planning of mobile robots working in partially known environments. Two steps constitute this approach. Firstly, free space model of mobile robot is established by using visible graph method and ACO algorithm is utilized in this model to
Xin Tan; Dingfang Chen
Comparison of the Event-Step Algorithm to Other Path Planning Methods to Avoid Dynamic 3D Obstacles.
In a previous paper, the Event-Step Algorithm (ESA) was presented as an efficient path planning algorithm to avoid dynamic obstacles. Dynamic obstacles are defined as obstacles that move and/or distort over time. Here, the focus is more closely on the alg...
M. Silbert
Enhanced phase unwrapping algorithm based on unscented Kalman filter, enhanced phase gradient estimator, and path-following strategy.
This paper presents an enhanced phase unwrapping algorithm by combining an unscented Kalman filter, an enhanced local phase gradient estimator based on an amended matrix pencil model, and a path-following strategy. This technology is able to accurately unwrap seriously noisy wrapped phase images by applying the unscented Kalman filter to simultaneously perform noise suppression and phase unwrapping along the path from the high-quality region to the low-quality region of the wrapped phase images. Results obtained with synthetic data and real data validate the effectiveness of the proposed method and show improved performance of this new algorithm with respect to some of the most used algorithms. PMID:24979440
Xie, XianMing; Li, YingHui
IPED: inheritance path-based pedigree reconstruction algorithm using genotype data.
The problem of inference of family trees, or pedigree reconstruction, for a group of individuals is a fundamental problem in genetics. Various methods have been proposed to automate the process of pedigree reconstruction given the genotypes or haplotypes of a set of individuals. Current methods, unfortunately, are very time-consuming and inaccurate for complicated pedigrees, such as pedigrees with inbreeding. In this work, we propose an efficient algorithm that is able to reconstruct large pedigrees with reasonable accuracy. Our algorithm reconstructs the pedigrees generation by generation, backward in time from the extant generation. We predict the relationships between individuals in the same generation using an inheritance path-based approach implemented with an efficient dynamic programming algorithm. Experiments show that our algorithm runs in linear time with respect to the number of reconstructed generations, and therefore, it can reconstruct pedigrees that have a large number of generations. Indeed it is the first practical method for reconstruction of large pedigrees from genotype data. PMID:24093229
He, Dan; Wang, Zhanyong; Han, Buhm; Parida, Laxmi; Eskin, Eleazar
An Algorithm for Traffic Grooming in WDM Mesh Networks Using Dynamic Path Selection Strategy
In wavelength-division multiplexing (WDM) optical networks, the bandwidth request of a traffic stream is generally much lower than the capacity of a lightpath. Therefore, to utilize the network resources (such as bandwidth and transceivers) effectively, several low-speed traffic streams can be efficiently groomed or multiplexed into high-speed lightpaths, thus we can improve the network throughput and reduce the network cost. The traffic grooming problem of a static demand is considered as an optimization problem. In this work, we have proposed a traffic grooming algorithm to maximize the network throughput and reduce the number of transceivers used for wavelength-routed mesh networks and also proposed a dynamic path selection strategy for routing requests which selects the path such that the load on the network gets distributed throughout. The efficiency of our approach has been established through extensive simulation on different sets of traffic demands with different bandwidth granularities for different network topologies and compared the approach with existing algorithm.
Bhattacharya, Sukanta; de, Tanmay; Pal, Ajit
Calculating Least Risk Paths in 3d Indoor Space
Over the last couple of years, research on indoor environments has gained a fresh impetus; more specifically applications that support navigation and wayfinding have become one of the booming industries. Indoor navigation research currently covers the technological aspect of indoor positioning and the modelling of indoor space. The algorithmic development to support navigation has so far been left mostly untouched, as most applications mainly rely on adapting Dijkstra's shortest path algorithm to an indoor network. However, alternative algorithms for outdoor navigation have been proposed adding a more cognitive notion to the calculated paths and as such adhering to the natural wayfinding behaviour (e.g. simplest paths, least risk paths). These algorithms are currently restricted to outdoor applications. The need for indoor cognitive algorithms is highlighted by a more challenged navigation and orientation due to the specific indoor structure (e.g. fragmentation, less visibility, confined areas…). As such, the clarity and easiness of route instructions is of paramount importance when distributing indoor routes. A shortest or fastest path indoors not necessarily aligns with the cognitive mapping of the building. Therefore, the aim of this research is to extend those richer cognitive algorithms to three-dimensional indoor environments. More specifically for this paper, we will focus on the application of the least risk path algorithm of Grum (2005) to an indoor space. The algorithm as proposed by Grum (2005) is duplicated and tested in a complex multi-storey building. The results of several least risk path calculations are compared to the shortest paths in indoor environments in terms of total length, improvement in route description complexity and number of turns. Several scenarios are tested in this comparison: paths covering a single floor, paths crossing several building wings and/or floors. Adjustments to the algorithm are proposed to be more aligned to the specific structure of indoor environments (e.g. no turn restrictions, restricted usage of rooms, vertical movement) and common wayfinding strategies indoors. In a later stage, other cognitive algorithms will be implemented and tested in both an indoor and combined indoor-outdoor setting, in an effort to improve the overall user experience during navigation in indoor environments.
Vanclooster, A.; De Maeyer, Ph.; Fack, V.; Van de Weghe, N.
An Improved Artificial Bee Colony Algorithm Based on Balance-Evolution Strategy for Unmanned Combat Aerial Vehicle Path Planning
Unmanned combat aerial vehicles (UCAVs) have been of great interest to military organizations throughout the world due to their outstanding capabilities to operate in dangerous or hazardous environments. UCAV path planning aims to obtain an optimal flight route with the threats and constraints in the combat field well considered. In this work, a novel artificial bee colony (ABC) algorithm improved by a balance-evolution strategy (BES) is applied in this optimization scheme. In this new algorithm, convergence information during the iteration is fully utilized to manipulate the exploration/exploitation accuracy and to pursue a balance between local exploitation and global exploration capabilities. Simulation results confirm that BE-ABC algorithm is more competent for the UCAV path planning scheme than the conventional ABC algorithm and two other state-of-the-art modified ABC algorithms.
Gong, Li-gang; Yang, Wen-lun
An improved artificial bee colony algorithm based on balance-evolution strategy for unmanned combat aerial vehicle path planning.
Unmanned combat aerial vehicles (UCAVs) have been of great interest to military organizations throughout the world due to their outstanding capabilities to operate in dangerous or hazardous environments. UCAV path planning aims to obtain an optimal flight route with the threats and constraints in the combat field well considered. In this work, a novel artificial bee colony (ABC) algorithm improved by a balance-evolution strategy (BES) is applied in this optimization scheme. In this new algorithm, convergence information during the iteration is fully utilized to manipulate the exploration/exploitation accuracy and to pursue a balance between local exploitation and global exploration capabilities. Simulation results confirm that BE-ABC algorithm is more competent for the UCAV path planning scheme than the conventional ABC algorithm and two other state-of-the-art modified ABC algorithms. PMID:24790555
Li, Bai; Gong, Li-Gang; Yang, Wen-Lun
Computing paths and cycles in biological interaction graphs
Background Interaction graphs (signed directed graphs) provide an important qualitative modeling approach for Systems Biology. They enable the analysis of causal relationships in cellular networks and can even be useful for predicting qualitative aspects of systems dynamics. Fundamental issues in the analysis of interaction graphs are the enumeration of paths and cycles (feedback loops) and the calculation of shortest positive/negative paths. These computational problems have been discussed only to a minor extent in the context of Systems Biology and in particular the shortest signed paths problem requires algorithmic developments. Results We first review algorithms for the enumeration of paths and cycles and show that these algorithms are superior to a recently proposed enumeration approach based on elementary-modes computation. The main part of this work deals with the computation of shortest positive/negative paths, an NP-complete problem for which only very few algorithms are described in the literature. We propose extensions and several new algorithm variants for computing either exact results or approximations. Benchmarks with various concrete biological networks show that exact results can sometimes be obtained in networks with several hundred nodes. A class of even larger graphs can still be treated exactly by a new algorithm combining exhaustive and simple search strategies. For graphs, where the computation of exact solutions becomes time-consuming or infeasible, we devised an approximative algorithm with polynomial complexity. Strikingly, in realistic networks (where a comparison with exact results was possible) this algorithm delivered results that are very close or equal to the exact values. This phenomenon can probably be attributed to the particular topology of cellular signaling and regulatory networks which contain a relatively low number of negative feedback loops. Conclusion The calculation of shortest positive/negative paths and cycles in interaction graphs is an important method for network analysis in Systems Biology. This contribution draws the attention of the community to this important computational problem and provides a number of new algorithms, partially specifically tailored for biological interaction graphs. All algorithms have been implemented in the CellNetAnalyzer framework which can be downloaded for academic use at .
Klamt, Steffen; von Kamp, Axel
An O(logn)Approximation Algorithm for the Disjoint Paths Problem in Eulerian Planar Graphs and 4-Edge-Connected Planar Graphs
\\u000a In this paper, we study an approximation algorithm for the maximum edge-disjoint paths problem. In the maximum edge-disjoint\\u000a paths problem, we are given a graph and a collection of pairs of vertices, and the objective is to find the maximum number\\u000a of pairs that can be connected by edge-disjoint paths. We give an O(logn)-approximation algorithm for the maximum edge-disjoint paths
Ken-ichi Kawarabayashiand; Yusuke Kobayashi
Fast two-dimensional phase-unwrapping algorithm based on sorting by reliability following a noncontinuous path.
We describe what is to our knowledge a novel technique for phase unwrapping. Several algorithms based on unwrapping the most-reliable pixels first have been proposed. These were restricted to continuous paths and were subject to difficulties in defining a starting pixel. The technique described here uses a different type of reliability function and does not follow a continuous path to perform the unwrapping operation. The technique is explained in detail and illustrated with a number of examples. PMID:12502301
Herráez, Miguel Arevallilo; Burton, David R; Lalor, Michael J; Gdeisat, Munther A
An Algorithm to Compute Statistics of Stochastic Paths on Complex Landscapes
Many systems in physics, chemistry, and biology can be modeled as a random walk on a network subject to a potential landscape. There is great interest in understanding the statistical properties of pathways on these landscapes, especially their times, lengths, and distributions in space. The complexity of the networks and landscapes arising in many models makes them difficult to solve by traditional analytical and computational tools. Moreover, standard methods do not always provide the most relevant information for characterizing these pathways. We develop an explicitly path-based formalism for studying these problems, which we implement using a numerical dynamic programming algorithm. It is especially well-suited to studying first-passage problems and rare transitions between metastable states. This method is valid for arbitrary networks and landscapes, as well as semi-Markovian processes with non-exponential waiting-time distributions. We explore this method on a variety of simple models including regular lattices, fractals, and protein sequence evolution.
Manhart, Michael; Morozov, Alexandre V.
Algorithms and novel applications based on the isokinetic ensemble. I. Biophysical and path integral molecular dynamics
In this paper (Paper I) and a companion paper (Paper II), novel new algorithms and applications of the isokinetic ensemble as generated by Gauss' principle of least constraint, pioneered for use with molecular dynamics 20 years ago, are presented for biophysical, path integral, and Car-Parrinello based ab initio molecular dynamics. In Paper I, a new ``extended system'' version of the isokinetic equations of motion that overcomes the ergodicity problems inherent in the standard approach, is developed using a new theory of non-Hamiltonian phase space analysis [M. E. Tuckerman et al., Europhys. Lett. 45, 149 (1999); J. Chem. Phys. 115, 1678 (2001)]. Reversible multiple time step integrations schemes for the isokinetic methods, first presented by Zhang [J. Chem. Phys. 106, 6102 (1997)] are reviewed. Next, holonomic constraints are incorporated into the isokinetic methodology for use in fast efficient biomolecular simulation studies. Model and realistic examples are presented in order to evaluate, critically, the performance of the new isokinetic molecular dynamic schemes. Comparisons are made to the, now standard, canonical dynamics method, Nosé-Hoover chain dynamics [G. J. Martyna et al., J. Chem. Phys. 97, 2635 (1992)]. The new isokinetic techniques are found to yield more efficient sampling than the Nosé-Hoover chain method in both path integral molecular dynamics and biophysical molecular dynamics calculations. In Paper II, the use of isokinetic methods in Car-Parrinello based ab initio molecular dynamics calculations is presented.
Minary, Peter; Martyna, Glenn J.; Tuckerman, Mark E.
A strategy for solving static multiple-optimal-path transit network problems
The trip making process using transit versus private automobile differs in the use of time schedules, walking paths, transfer stops, plus issues such as fare and safety. Due to these factors, many of the standard shortest path algorithms do not apply. The purpose of this study is to develop an algorithm and strategy for transit providers to find best alternatives for the user, and to demonstrate how a geographic information system can be used in the development of transit advanced traveler information system (TATIS) to meet these needs. This paper presents a short introduction to TATIS systems, some commonly used algorithms in determining the shortest and multiple paths, and a new strategy that was developed in this study which differs from standard network algorithms. The major features of this proposed algorithm are: (1) Capability of handling multiple modes of transit; (2) providing paths that include walking distances from and to the transit path as well as between transfer points; and (3) provision of multiple optimal paths to allow the user flexibility in choosing a path.
Koncz, N.; Greenfeld, J.; Mouskos, K. [New Jersey Inst. of Tech., Newark, NJ (United States). Dept. of Civil Engineering
Worm algorithm and diagrammatic Monte Carlo: A new approach to continuous-space path integral Monte Carlo simulations
A detailed description is provided of a new worm algorithm, enabling the accurate computation of thermodynamic properties of quantum many-body systems in continuous space, at finite temperature. The algorithm is formulated within the general path integral Monte Carlo (PIMC) scheme, but also allows one to perform quantum simulations in the grand canonical ensemble, as well as to compute off-diagonal imaginary-time
M. Boninsegni; N. V. Prokof'Ev; B. V. Svistunov
Bandwidth Allocation for Virtual Paths (BAVP): Investigation of Performance of Classical Constrained and Genetic Algorithm Based Optimisation Techniques
We investigate the performance of a classical constrained optimisation (CCO) algorithm and a constrained optimisation Genetic Algorithm (GA) for solving the Bandwidth Allocation for Virtual Paths (BAVP) problem. We compare throughput, fairness and time complexity of GA-BAVP and CCO-BAVP for several node topologies. The results on maximising the throughput obtained with GA-BAVP and CCO- BAVP are in close agreement, however
Andreas Pitsillides; George Stylianou; Constantinos S. Pattichis; Y. Ahmet Sekercioglu; Athanasios V. Vasilakos
3-D path planning for the navigation of unmanned aerial vehicles by using evolutionary algorithms
Military missions are turning to more complicated and advanced automation technology for maximum endurance and efficiency as well as the minimum vital risks. The path planners which generate collision-free and optimized paths are needed to give autonomous operation capability to the Unmanned Aerial Vehicles (UAVs). This paper presents an off-line path planner for UAVs. The path planner is based on
Isil Hasircioglu; Haluk Rahmi Topcuoglu; Murat Ermis
Spreading paths in partially observed social networks
Understanding how and how far information, behaviors, or pathogens spread in social networks is an important problem, having implications for both predicting the size of epidemics, as well as for planning effective interventions. There are, however, two main challenges for inferring spreading paths in real-world networks. One is the practical difficulty of observing a dynamic process on a network, and the other is the typical constraint of only partially observing a network. Using a static, structurally realistic social network as a platform for simulations, we juxtapose three distinct paths: (1) the stochastic path taken by a simulated spreading process from source to target; (2) the topologically shortest path in the fully observed network, and hence the single most likely stochastic path, between the two nodes; and (3) the topologically shortest path in a partially observed network. In a sampled network, how closely does the partially observed shortest path (3) emulate the unobserved spreading path (1)? Although partial observation inflates the length of the shortest path, the stochastic nature of the spreading process also frequently derails the dynamic path from the shortest path. We find that the partially observed shortest path does not necessarily give an inflated estimate of the length of the process path; in fact, partial observation may, counterintuitively, make the path seem shorter than it actually is.
Onnela, Jukka-Pekka; Christakis, Nicholas A.
Application of A* algorithm for real-time path re-planning of an unmanned surface vehicle avoiding underwater obstacles
This paper describes path re-planning techniques and underwater obstacle avoidance for unmanned surface vehicle (USV) based on multi-beam forward looking sonar (FLS). Near-optimal paths in static and dynamic environments with underwater obstacles are computed using a numerical solution procedure based on an A* algorithm. The USV is modeled with a circular shape in 2 degrees of freedom (surge and yaw). In this paper, two-dimensional (2-D) underwater obstacle avoidance and the robust real-time path re-planning technique for actual USV using multi-beam FLS are developed. Our real-time path re-planning algorithm has been tested to regenerate the optimal path for several updated frames in the field of view of the sonar with a proper update frequency of the FLS. The performance of the proposed method was verified through simulations, and sea experiments. For simulations, the USV model can avoid both a single stationary obstacle, multiple stationary obstacles and moving obstacles with the near-optimal trajectory that are performed both in the vehicle and the world reference frame. For sea experiments, the proposed method for an underwater obstacle avoidance system is implemented with a USV test platform. The actual USV is automatically controlled and succeeded in its real-time avoidance against the stationary undersea obstacle in the field of view of the FLS together with the Global Positioning System (GPS) of the USV.
Phanthong, Thanapong; Maki, Toshihiro; Ura, Tamaki; Sakamaki, Takashi; Aiyarak, Pattara
A Faster Strongly Polynomial Minimum Cost Flow Algorithm
In this paper, we present a new strongly polynomial time algorithm for the minimum cost flow problem, based on a refinement of the Edmonds-Karp scaling technique. Our algorithm solves the uncapacitated minimum cost flow problem as a sequence of O(n log n) shortest path problems on networks with n nodes and m arcs and runs in O(n log n (m
A computational study of routing algorithms for realistic transportation networks
The authors carry out an experimental analysis of a number of shortest path (routing) algorithms investigated in the context of the TRANSIMS (Transportation Analysis and Simulation System) project. The main focus of the paper is to study how various heuristic and exact solutions, associated data structures affected the computational performance of the software developed especially for realistic transportation networks. For this purpose the authors have used Dallas Fort-Worth road network with very high degree of resolution. The following general results are obtained: (1) they discuss and experimentally analyze various one-one shortest path algorithms, which include classical exact algorithms studied in the literature as well as heuristic solutions that are designed to take into account the geometric structure of the input instances; (2) they describe a number of extensions to the basic shortest path algorithm. These extensions were primarily motivated by practical problems arising in TRANSIMS and ITS (Intelligent Transportation Systems) related technologies. Extensions discussed include--(i) time dependent networks, (ii) multi-modal networks, (iii) networks with public transportation and associated schedules. Computational results are provided to empirically compare the efficiency of various algorithms. The studies indicate that a modified Dijkstra`s algorithm is computationally fast and an excellent candidate for use in various transportation planning applications as well as ITS related technologies.
Jacob, R.; Marathe, M.V.; Nagel, K.
Rapid path-planning algorithms for autonomous proximity operations of satellites
Autonomous proximity operations (APOs) can be bifurcated into two phases: (i) close-range rendezvous and (ii) final approach or endgame. For each APO phase, algorithms capable of real-time path planning provide the greatest ability to react to "unmodeled" events, thus enabling the highest level of autonomy. This manuscript explores methodologies for real-time computation of APO trajectories for both APO phases. For the close-range rendezvous trajectories, an Adaptive Artificial Potential Function (AAPF) methodology is developed. The AAPF method is a modification of the Artificial Potential Function (APF) methodology which has favorable convergence characteristics. Building on these characteristics, the modification involves embedding the system dynamics and a performance criterion into the APF formulation resulting in a tunable system. Near-minimum time and/or near-minimum fuel trajectories are obtained by selecting the tuning parameter. Monte Carlo simulations are performed to assess the performance of the AAPF methodology. For the final approach or endgame trajectories, two methodologies are considered: a Picard Iteration (PI) and a Homotopy Continuation (HC). Problems in this APO phase are typically solved as a finite horizon linear quadratic (LQ) problem, which essentially are solved as a final value problem with a Differential Riccati Equation (DRE). The PI and HC methods are well known tools for solving differential equations and are utilized in this effort to provide solutions to the DRE which are amenable to real-time implementations; i.e., they provide solutions which are functionals to be evaluated real-time. Several cases are considered and compared to the classical DRE solution.
Munoz, Josue David
Optimal parallel algorithms for problems modeled by a family of intervals
A family of intervals on the real line provides a natural model for a vast number of scheduling and VLSI problems. Recently, a number of parallel algorithms to solve a variety of practical problems on such a family of intervals have been proposed in the literature. Computational tools are developed, and it is shown how they can be used for the purpose of devising cost-optimal parallel algorithms for a number of interval-related problems including finding a largest subset of pairwise nonoverlapping intervals, a minimum dominating subset of intervals, along with algorithms to compute the shortest path between a pair of intervals and, based on the shortest path, a parallel algorithm to find the center of the family of intervals. More precisely, with an arbitrary family of n intervals as input, all algorithms run in O(log n) time using O(n) processors in the EREW-PRAM model of computation.
Olariu, Stephan; Schwing, James L.; Zhang, Jingyuan
An Efficient Global Optimization Approach to Multi Robot Path Exploration Problem Using Hybrid Genetic Algorithm
This paper presents a novel scheme for global path exploration to multi robots environment using hybrid implementation of evolutionary heuristic. This scheme is used to find an optimal path for each mobile robot to move in a static environment expressed by a weighted graph with nodes and links. The interesting part of this scheme is that the chromosome structure is
K. S. Senthilkumar; K. K. Bharadwaj
Shortest Path Search in Multi-Representation Street Databases
The fact that mobile users of location-based services (LBS) have to be able to go anywhere on earth without changing the application\\u000a brings up a major requirement: there has to be one global platform that provides a transborder and continuous access to the\\u000a information necessary for this kind of information systems — and the most important information source for location-based
Steffen Volz
Scientific collaboration networks. II. Shortest paths, weighted networks, and centrality
Using computer databases of scientific papers in physics, biomedical research, and computer science, we have constructed networks of collaboration between scientists in each of these disciplines. In these networks two scientists are considered connected if they have coauthored one or more papers together. Here we study a variety of nonlocal statistics for these networks, such as typical distances between scientists
M. E. J. Newman
Visibility-Polygon Search and Euclidean Shortest Paths
Consider a collection of disjoint polygons in the plane containing a total of n edges. We show how to build, in O(n2) time and space, a data structure from which in O(n) time we can compute the visibility polygon of a given point with respect to the polygon collection. As an application of this structure, the visibility graph of the
Takao Asano; Tetsuo Asano; Leonidas J. Guibas; John Hershberger; Hiroshi Imai
Shortest Paths in Stochastic Networks with Correlated Link Costs
Abstract. The objective is to minimize,expected travel time from any origin to a specific destination in a congestible network with correlated link costs. Each link is assumed,to bein,one of two,possible conditions. Conditional probability density functions for link travel times are assumed,known,for each condition. Conditions over the traversed links are taken into account for determining the optimal routing strategy for the
Membrane Boundary Extraction Using a Circular Shortest Path Technique
Membrane proteins represent over 50% of known drug targets. Accordingly, several widely used assays in the High Content Analysis area rely on quantitative measures of the translocation of proteins between intracellular organelles and the cell surface. In order to increase the sensitivity of these assays, one needs to measure the signal specifically along the membrane, requiring a precise segmentation of
Changming Sun; Pascal Vallotton; Dadong Wang; Jamie Lopez; Yvonne Ng; David James
Fast shortest path distance estimation in large networks
In this paper we study approximate landmark-based meth- ods for point-to-point distance estimation in very large net- works. These methods involve selecting a subset of nodes as landmarks and computing offline the distances from each node in the graph to those landmarks. At runtime, when the distance between a pair of nodes is needed, it can be estimated quickly by
Michalis Potamias; Francesco Bonchi; Carlos Castillo; Aristides Gionis
An Optimal Transit Path Algorithm Based on the Terminal Walking Time Judgment and Multimode Transit Schedules
The optimal transit path needs to be re-recognized and analyzed in the multi-mode transit system. This paper constructs the transit network data model of multi-mode and multi-property using the function of space analyzing of GIS, and establish the general impedance function considering the impact of reasonable terminal walking range, transfer time, and transit schedule for the trip path, and presents
Zhu Shunying; Yan Yongfei; Wang Hong; Li Shangbin
Fast distributed and parallel algorithms for data network control problems
Analysis of existing algorithms, as well as the development and analysis of new algorithms/techniques for solving network control problems are presented. First, an upper bound for the time complexity of the path formulated gradient projection algorithm (for solving the optimal routing problem in large data networks) is derived. The complexity bound is expressed in terms of the size of the network and the total amount of traffic demand. Also, a new distributed shortest path algorithm is developed for a class of hierarchically structured data networks. The time complexity of this new algorithm is generically better than any known distributed shortest path algorithm. Next, the method of aggregation/disaggregation is applied to the gradient projection algorithm and is shown to have the potential of speeding up the rate of convergence. Finally, a novel parallel algorithm is developed for solving the multistage optimization problem. It is shown that this new parallel algorithm achieves a better time complexity than the standard dynamic programming approach of solving the multistage optimization problem.
Antonio, J.K.
Adaptive Routing Algorithm in Wireless Communication Networks Using Evolutionary Algorithm
At present, mobile communications traffic routing designs are complicated because there are more systems inter-connecting to one another. For example, Mobile Communication in the wireless communication networks has two routing design conditions to consider, i.e. the circuit switching and the packet switching. The problem in the Packet Switching routing design is its use of high-speed transmission link and its dynamic routing nature. In this paper, Evolutionary Algorithms is used to determine the best solution and the shortest communication paths. We developed a Genetic Optimization Process that can help network planners solving the best solutions or the best paths of routing table in wireless communication networks are easily and quickly. From the experiment results can be noted that the evolutionary algorithm not only gets good solutions, but also a more predictable running time when compared to sequential genetic algorithm.
Yan, Xuesong; Wu, Qinghua; Cai, Zhihua
Path Tracking using Vector Pursuit Algorithm for Tracked Vehicles Driving on the Soft Cohesive Soil
Generally, tracked vehicles are used in military, agricultural and recreational applications where terrain conditions are improper or unpredictable. Tracked vehicles are better than wheeled vehicles due to the larger contact area of tracks providing better floatation and traction at various ground conditions. In this paper, the path tracking method is proposed for tracked vehicle driving on the deep-sea soft cohesive
Tae-Kyeong Yeul; Soung-Jea Park; Sup Hong; Hyung-Woo Kim; Jong-Su Choi
Automatic test data generation for path testing using a new stochastic algorithm
Software testing is an important activity of the software development process, and automate test data generation contributes to reduce cost and time efforts. Path testing is a complex problem and metaheuristics have been pro- posed to deal with it. In this paper, an initial assessment of the efficacy of a re- cently proposed metaheuristic, the Generalized Extremal Optimization (GEO), in
Bruno T. de Abreu; Eliane Martins; Fabiano L. de Sousa
A cooperative coevolutionary algorithm for the design of wireless sensor networks: track name: bio-inspired solutions for wireless sensor networks
This work proposes a cooperative coevolutionary algorithm for the design of a wireless sensor network considering complex network metrics. It is proposed an heuristic based on cooperative coevolution to find a network configuration such that its communication structure presents a small value for the average shortest path length and a high cluster coefficient. This configuration considers a cluster based network,
André Siqueira Ruela; André Luiz Lins Aquino; Frederico Gadelha Guimarăes
A Linear Algorithm for the Pos\\/Neg-Weighted 1Median Problem on a Cactus
The 1-median problem on a network asks for a vertex minimizing the sum of the weighted shortest path distances from itself\\u000a to all other vertices, each associated with a certain positive weight. We allow fornegative weights as well and devise an exact algorithm for the resulting 'pos\\/neg-weighted' problem defined on a cactus. The algorithm\\u000a visits every vertex just once and
Rainer E. Burkard; Jakob Krarup
Efficient parallel algorithms for testing connectivity and finding disjoint s-t paths in graphs
An efficient parallel algorithm for testing whether a graph G is K-vertex connected, for any fixed k, is presented. The algorithm runs in O(log n) time and uses nC(n,m) processors on a concurrent-read, concurrent-write parallel random-access machine (CRCW PRAM), where n and m are the number of vertices and edges of G and C(n,m) is the number of processors required
Samir Khuller; Baruch Schieber
Efficient algorithms for semiclassical instanton calculations based on discretized path integrals.
Path integral instanton method is a promising way to calculate the tunneling splitting of energies for degenerated two state systems. In order to calculate the tunneling splitting, we need to take the zero temperature limit, or the limit of infinite imaginary time duration. In the method developed by Richardson and Althorpe [J. Chem. Phys. 134, 054109 (2011)], the limit is simply replaced by the sufficiently long imaginary time. In the present study, we have developed a new formula of the tunneling splitting based on the discretized path integrals to take the limit analytically. We have applied our new formula to model systems, and found that this approach can significantly reduce the computational cost and gain the numerical accuracy. We then developed the method combined with the electronic structure calculations to obtain the accurate interatomic potential on the fly. We present an application of our ab initio instanton method to the ammonia umbrella flip motion. PMID:25027993
Kawatsu, Tsutomu; Miura, Shinichi
FPGA Implementation of Genetic Algorithm for UAV Real-Time Path Planning
The main objective of an Unmanned-Aerial-Vehicle (UAV) is to provide an operator with services from its payload. Currently,\\u000a to get these UAV services, one extra human operator is required to navigate the UAV. Many techniques have been investigated\\u000a to increase UAV navigation autonomy at the Path Planning level. The most challenging aspect of this task is the re-planning\\u000a requirement, which
François C. J. Allaire; Mohamed Tarbouchi; Gilles Labonté; Giovanni Fusina
PathGrid: The Transfer of Astronomical Image Algorithms to the Analysis of Medical Microscopy Data
We describe our pilot `PathGrid' study which applies astronomical image processing and data handling techniques to the challenges involved in analysing Tissue Micro Array (TMA) image data. Image analysis has been applied to the input TMA data using open source solutions developed for an astronomical context. The resulting data products are in turn interfaced to the clinical trials systems in use at the Cambridge Research Institute (Cancer Research-UK).
Walton, N. A.; Brenton, J. D.; Caldas, C.; Irwin, M. J.; Akram, A.; Gonzalez-Solares, E.; Lewis, J. R.; MacCullum, P.; Morris, L. J.; Rixon, G. T.
I\\/O-Optimal Algorithms for Outerplanar Graphs
We present linear-I\\/O algorithms for fundamental graph problems on em- bedded outerplanar graphs. We show that breadth-first search, depth-first search, single-source shortest paths, triangulation, and computing an ? - separator of size O(1\\/? )t akeO(scan(N)) I\\/Os on embedded outerplanar graphs. We also show that it takes O(sort(N)) I\\/Os to test whether a given graph is outerplanar and to compute an
Anil Maheshwari; Norbert Zeh
A dynamic programming algorithm applied to track initiation
An approach for initiating tracks for multiple target tracking is presented. A means of using a graph to represent objects moving in a sequence of images is given. The approach for initiating tracks is based on a dynamic programming algorithm for finding the shortest path in the graph. For comparison purposes an extensive optimal solution and other practical track initiation approaches from the open literature are discussed. 7 refs., 7 figs.
Coleman, D.E.
Loop-Free Hybrid Single-Path\\/Flooding Routing Algorithms with Guaranteed Delivery for Wireless Networks
In a localized routing algorithm, each node makes forwarding decisions solely based on the position of itself, its neighbors, and its destination. In distance, progress, and direction-based approaches (reported in the literature), when node A wants to send or forward message m to destination node D, it forwards m to its neighbor C which is closest to D (has best
Ivan Stojmenovic; Xu Lin
Constraint-Based Local Search for Constrained Optimum Paths Problems
Constrained Optimum Path (COP) problems arise in many real-life applications and are ubiquitous in communication networks. They have been traditionally approached by dedicated algorithms, which are often hard to extend with side constraints and to apply widely. This paper proposes a constraint-based local search (CBLS) framework for COP applications, bringing the compositionality, reuse, and extensibility at the core of CBLS and CP systems. The modeling contribution is the ability to express compositional models for various COP applications at a high level of abstraction, while cleanly separating the model and the search procedure. The main technical contribution is a connected neighborhood based on rooted spanning trees to find high-quality solutions to COP problems. The framework, implemented in COMET, is applied to Resource Constrained Shortest Path (RCSP) problems (with and without side constraints) and to the edge-disjoint paths problem (EDP). Computational results show the potential significance of the approach.
Pham, Quang Dung; Deville, Yves; van Hentenryck, Pascal
Information Spread of Emergency Events: Path Searching on Social Networks
Emergency has attracted global attentions of government and the public, and it will easily trigger a series of serious social problems if it is not supervised effectively in the dissemination process. In the Internet world, people communicate with each other and form various virtual communities based on social networks, which lead to a complex and fast information spread pattern of emergency events. This paper collects Internet data based on data acquisition and topic detection technology, analyzes the process of information spread on social networks, describes the diffusions and impacts of that information from the perspective of random graph, and finally seeks the key paths through an improved IBF algorithm. Application cases have shown that this algorithm can search the shortest spread paths efficiently, which may help us to guide and control the information dissemination of emergency events on early warning.
Hu, Hongzhi; Wu, Tunan
Methodology for Augmenting Existing Paths with Additional Parallel Transects
Visual Sample Plan (VSP) is sample planning software that is used, among other purposes, to plan transect sampling paths to detect areas that were potentially used for munition training. This module was developed for application on a large site where existing roads and trails were to be used as primary sampling paths. Gap areas between these primary paths needed to found and covered with parallel transect paths. These gap areas represent areas on the site that are more than a specified distance from a primary path. These added parallel paths needed to optionally be connected together into a single path—the shortest path possible. The paths also needed to optionally be attached to existing primary paths, again with the shortest possible path. Finally, the process must be repeatable and predictable so that the same inputs (primary paths, specified distance, and path options) will result in the same set of new paths every time. This methodology was developed to meet those specifications.
Wilson, John E.
A detailed description is provided of a new worm algorithm, enabling the accurate computation of thermodynamic properties of quantum many-body systems in continuous space, at finite temperature. The algorithm is formulated within the general path integral Monte Carlo (PIMC) scheme, but also allows one to perform quantum simulations in the grand canonical ensemble, as well as to compute off-diagonal imaginary-time correlation functions, such as the Matsubara Green function, simultaneously with diagonal observables. Another important innovation consists of the expansion of the attractive part of the pairwise potential energy into elementary (diagrammatic) contributions, which are then statistically sampled. This affords a complete microscopic account of the long-range part of the potential energy, while keeping the computational complexity of all updates independent of the size of the simulated system. The computational scheme allows for efficient calculations of the superfluid fraction and off-diagonal correlations in space-time, for system sizes which are orders of magnitude larger than those accessible to conventional PIMC. We present illustrative results for the superfluid transition in bulk liquid {sup 4}He in two and three dimensions, as well as the calculation of the chemical potential of hcp {sup 4}He.
Boninsegni, M. [Department of Physics, University of Alberta, Edmonton, Alberta, Canada T6G 2J1 (Canada); Prokof'ev, N. V. [Department of Physics, University of Massachusetts, Amherst, Massachusetts 01003 (United States); BEC-INFM, Dipartimento di Fisica, Universita di Trento, Via Sommarive 14, I-38050 Povo (Italy); Russian Research Center, Kurchatov Institute, 123182 Moscow (Russian Federation); Svistunov, B. V. [Department of Physics, University of Massachusetts, Amherst, Massachusetts 01003 (United States); Russian Research Center, Kurchatov Institute, 123182 Moscow (Russian Federation)
Data Generation for Path Testing
We present two stochastic search algorithms for generating test cases that execute specified paths in a program. The two algorithms are: a simulated annealing algorithm (SA), and a genetic algorithm (GA). These algorithms are based on an optimization formulation of the path testing problem which include both integer- and real-value test cases. We empirically compare the SA and GA algorithms
Nashat Mansour; Miran Salame
Estimating Critical Path and Arc Probabilities in Stochastic Activity Networks.
This paper describes a new procedure for estimating parameters of a stochastic activity network of N arcs. The parameters include the probability that path m is the longest path, the probability that path m is the shortest path, the probability that arc i...
G. S. Fishman
Path planning for UAVs
In this paper, a two step path-planning algorithm for UAVs is proposed. The algorithm generates a stealthy path through a set of enemy radar sites of known location, and provides an intuitive way to trade-off stealth versus path length. In the first step, a suboptimal rough-cut path is generated through the radar sites by constructing and searching a graph based
S. A. Bortoff; E. Hartford
Phase unwrapping for SAR interferometry based on an ant colony optimization algorithm
Phase unwrapping is a key step in extracting digital elevation models (DEMs) from interferometric synthetic aperture radar (InSAR) data. A new two?dimensional (2?D) phase unwrapping algorithm based on ant colony optimization (ACO) is proposed, which is used to configure the shortest path linking all residues in an interferogram. Using an optimization strategy to establish the branch cuts, the unwrapping error
F. Xu
A new graph model and algorithms for consistent superstring problems.
Problems related to string inclusion and non-inclusion have been vigorously studied in diverse fields such as data compression, molecular biology and computer security. Given a finite set of positive strings and a finite set of negative strings , a string ? is a consistent superstring if every positive string is a substring of ? and no negative string is a substring of ?. The shortest (resp. longest) consistent superstring problem is to find a string ? that is the shortest (resp. longest) among all the consistent superstrings for the given sets of strings. In this paper, we first propose a new graph model for consistent superstrings for given and . In our graph model, the set of strings represented by paths satisfying some conditions is the same as the set of consistent superstrings for and . We also present algorithms for the shortest and the longest consistent superstring problems. Our algorithms solve the consistent superstring problems for all cases, including cases that are not considered in previous work. Moreover, our algorithms solve in polynomial time the consistent superstring problems for more cases than the previous algorithms. For the polynomially solvable cases, our algorithms are more efficient than the previous ones. PMID:24751868
Na, Joong Chae; Cho, Sukhyeun; Choi, Siwon; Kim, Jin Wook; Park, Kunsoo; Sim, Jeong Seop
A labeling algorithm for the navigation of automated guided vehicles
Material handling is an important component of most automated manufacturing systems. AGVs are commonly employed for this function. Efficient use of the AGV system requires proper routing and scheduling of vehicular traffic. This problem is modeled as a shortest path problem with multiple time windows on arcs and at nodes of a network. A polynomial-time labeling algorithm has been developed. The algorithm has complexity O (D[sup 2]log[sub d]D), where D is the total number of time windows in the problem. The data required for the model is easy to maintain.
Huang, J.; Palekar, U.S.; Kapoor, S.G. (Univ. of Illinois, Urbana, IL (United States). Dept. of Mechanical and Industrial Engineering)
A fast algorithm for computing geodesic distances in tree space.
Comparing and computing distances between phylogenetic trees are important biological problems, especially for models where edge lengths play an important role. The geodesic distance measure between two phylogenetic trees with edge lengths is the length of the shortest path between them in the continuous tree space introduced by Billera, Holmes, and Vogtmann. This tree space provides a powerful tool for studying and comparing phylogenetic trees, both in exhibiting a natural distance measure and in providing a euclidean-like structure for solving optimization problems on trees. An important open problem is to find a polynomial time algorithm for finding geodesics in tree space. This paper gives such an algorithm, which starts with a simple initial path and moves through a series of successively shorter paths until the geodesic is attained. PMID:21071792
Owen, Megan; Provan, J Scott
Flight tests of three-dimensional path-redefinition algorithms for transition from Radio Navigation (RNAV) to Microwave Landing System (MLS) navigation when flying an aircraft on autopilot
This report contains results of flight tests for three path update algorithms designed to provide smooth transition for an aircraft guidance system from DME, VORTAC, and barometric navaids to the more precise MLS by modifying the desired 3-D flight path. The first algorithm, called Zero Cross Track, eliminates the discontinuity in cross-track and altitude error at transition by designating the first valid MLS aircraft position as the desired first waypoint, while retaining all subsequent waypoints. The discontinuity in track angle is left unaltered. The second, called Tangent Path, also eliminates the discontinuity in cross-track and altitude errors and chooses a new desired heading to be tangent to the next oncoming circular arc turn. The third, called Continued Track, eliminates the discontinuity in cross-track, altitude, and track angle errors by accepting the current MLS position and track angle as the desired ones and recomputes the location of the next waypoint. The flight tests were conducted on the Transportation Systems Research Vehicle, a small twin-jet transport aircraft modified for research under the Advanced Transport Operating Systems program at Langley Research Center. The flight tests showed that the algorithms provided a smooth transition to MLS.
Hueschen, Richard M.
A QoS Based Routing Algorithm for Multi-class Optimization in DiffServ Networks
\\u000a DiffServ has been proposed as a scalable model to offer various quality of services (QoS) in the Internet. It supports diverse\\u000a traffic classes with different priorities. However, recent work has discovered that high priority classes (e.g., EF class)\\u000a have significant impact on the performance of low priority classes (e.g., BE class) when traditional shortest path (SP) routing\\u000a algorithms are applied.
Wenpeng Zhou; Peng Zhang; Xiaole Bai; Raimo Kantola
Determination of the optimal load path for tube hydroforming processes using a fuzzy load control algorithm and finite element analysis
In the tube hydroforming process, the formability of a metallic tube is directly affected by the forming load path (i.e. axial feed and internal hydroforming pressure). Most tube hydroformed parts are produced by a multistage loading process. The forming limit strains induced during the actual forming operation are therefore path dependent. This paper discusses the optimisation of the forming load
P. Ray; B. J. Mac Donald
Efficient Algorithms and Data Structures for Massive Data Sets
For many algorithmic problems, traditional algorithms that optimise on the number of instructions executed prove expensive on I/Os. Novel and very different design techniques, when applied to these problems, can produce algorithms that are I/O efficient. This thesis adds to the growing chorus of such results. The computational models we use are the external memory model and the W-Stream model. On the external memory model, we obtain the following results. (1) An I/O efficient algorithm for computing minimum spanning trees of graphs that improves on the performance of the best known algorithm. (2) The first external memory version of soft heap, an approximate meldable priority queue. (3) Hard heap, the first meldable external memory priority queue that matches the amortised I/O performance of the known external memory priority queues, while allowing a meld operation at the same amortised cost. (4) I/O efficient exact, approximate and randomised algorithms for the minimum cut problem, which has not been explored before on the external memory model. (5) Some lower and upper bounds on I/Os for interval graphs. On the W-Stream model, we obtain the following results. (1) Algorithms for various tree problems and list ranking that match the performance of the best known algorithms and are easier to implement than them. (2) Pass efficient algorithms for sorting, and the maximal independent set problems, that improve on the best known algorithms. (3) Pass efficient algorithms for the graphs problems of finding vertex-colouring, approximate single source shortest paths, maximal matching, and approximate weighted vertex cover. (4) Lower bounds on passes for list ranking and maximal matching. We propose two variants of the W-Stream model, and design algorithms for the maximal independent set, vertex-colouring, and planar graph single source shortest paths problems on those models.
Intelligent Recommender System Using Shopper's Path and Purchase Analysis
Shoppers having a predefined shopping list usually follow the shortest path through a supermarket or store in order to make their purchases. This paper aims to study customer behaviour of such shoppers with respect to two aspects: (1) the path followed through the store to make those purchases. (2) the average path length to make those purchases. The paper also
Anala A Pandit; Jyot Talreja; M. Agrawal; Deepak Prasad; Swati Baheti; G. Khalsa
A reconfigurable multiprocessor IC for rapid prototyping of algorithmic-specific high-speed DSP data paths
A field-programmable multiprocessor integrated circuit, PADDI (programmable arithmetic devices for high-speed digital signal processing), has been designed for the rapid prototyping of high-speed data paths typical to real-time digital signal processing applications. The processor architecture addresses the key requirements of these data paths: (a) fast, concurrently operating, multiple arithmetic units, (b) conflict-free data routing, (c) moderate hardware multiplexing (of the
Dev C. Chen; Jan M. Rabaey
Adaptive DNA Computing Algorithm by Using PCR and Restriction Enzyme
In this paper, we introduce an adaptive DNA computing algorithm by using polymerase chain reaction (PCR) and restriction enzyme. The adaptive algorithm is designed based on Adleman-Lipton paradigm[3] of DNA computing. In this work, however, unlike the Adleman- Lipton architecture a cutting operation has been introduced to the algorithm and the mechanism in which the molecules used by computation were feedback to the next cycle devised. Moreover, the amplification by PCR is performed in the molecule used by feedback and the difference concentration arisen in the base sequence can be used again. By this operation the molecules which serve as a solution candidate can be reduced down and the optimal solution is carried out in the shortest path problem. The validity of the proposed adaptive algorithm is considered with the logical simulation and finally we go on to propose applying adaptive algorithm to the chemical experiment which used the actual DNA molecules for solving an optimal network problem.
Kon, Yuji; Yabe, Kaoru; Rajaee, Nordiana; Ono, Osamu
A unifying graph-cut image segmentation framework: algorithms it encompasses and equivalences among them
We present a general graph-cut segmentation framework GGC, in which the delineated objects returned by the algorithms optimize the energy functions associated with the lp norm, 1 <= p <= ?. Two classes of well known algorithms belong to GGC: the standard graph cut GC (such as the min-cut/max-flow algorithm) and the relative fuzzy connectedness algorithms RFC (including iterative RFC, IRFC). The norm-based description of GGC provides more elegant and mathematically better recognized framework of our earlier results from [18, 19]. Moreover, it allows precise theoretical comparison of GGC representable algorithms with the algorithms discussed in a recent paper [22] (min-cut/max-flow graph cut, random walker, shortest path/geodesic, Voronoi diagram, power watershed/shortest path forest), which optimize, via lp norms, the intermediate segmentation step, the labeling of scene voxels, but for which the final object need not optimize the used lp energy function. Actually, the comparison of the GGC representable algorithms with that encompassed in the framework described in [22] constitutes the main contribution of this work.
Ciesielski, Krzysztof Chris; Udupa, Jayaram K.; Falcăo, A. X.; Miranda, P. A. V.
Path integral Monte Carlo approach for weakly bound van der Waals complexes with rotations: Algorithm and benchmark calculations
A path integral Monte Carlo technique suitable for the treatment of doped helium clusters with inclusion of the rotational degrees of freedom of the dopant is introduced. The extrapolation of the results to the limit of infinite Trotter number is discussed in detail. Benchmark calculations for small weakly bound 4HeN-OCS clusters are presented. The Monte Carlo results are compared with
Nicholas Blinov; Xiaogeng Song; Pierre-Nicholas Roy
Path similarity skeleton graph matching.
This paper presents a novel framework to for shape recognition based on object silhouettes. The main idea is to match skeleton graphs by comparing the shortest paths between skeleton endpoints. In contrast to typical tree or graph matching methods, we completely ignore the topological graph structure. Our approach is motivated by the fact that visually similar skeleton graphs may have completely different topological structures. The proposed comparison of shortest paths between endpoints of skeleton graphs yields correct matching results in such cases. The skeletons are pruned by contour partitioning with Discrete Curve Evolution, which implies that the endpoints of skeleton branches correspond to visual parts of the objects. The experimental results demonstrate that our method is able to produce correct results in the presence of articulations, stretching, and occlusion. PMID:18550909
Bai, Xiang; Latecki, Longin Jan
Two-shot common-path phase-shifting interferometer with a four-step algorithm and an unknown phase shift.
This paper presents a two-shot common-path phase-shifting interferometer that consists of a 4f optical system with two windows in the input plane and a Ronchi grating in the Fourier plane, and generates two adjacent interferograms using only diffraction orders 0 and +1 and 0 and -1. Four phase-shifted interferograms can be obtained in two shots by modulating two linear polarizers with angle difference of ?/4 and translating the grating with only an unknown phase shift. An algorithm similar to the standard four-step algorithm is used to retrieve the phase of a specimen, and it requires no knowledge of the phase shift introduced by translation of the grating. The validity and repeatability of the proposed method is proved through simulations and experiments. PMID:24787163
Zhong, Zhi; Hao, Bengong; Shan, Mingguang; Wang, Ying; Diao, Ming; Zhang, Yabin
Solving graph algorithms with networks of spiking neurons.
Spatio-temporal coding that combines spatial constraints with temporal sequencing is of great interest to brain-like circuit modelers. In this paper we present some new ideas of how these types of circuits can self-organize. We introduce a temporal correlation rule based on the time difference between the firings of neurons.With the aid of this rule we show an analogy between a graph and a network of spiking neurons. The shortest path, clustering based on the nearest neighbor, and the minimal spanning tree algorithms are solved using the proposed approach. PMID:18252594
Sala, D M; Cios, K J
Fast computation algorithm of ray-paths and their travel times including later arrivals for a multi layered earth model
Seismic tomography techniques have been rapidly developed to interpret crustal seismic refraction data. Forward modeling approaches, however, are also necessary to examine an initial model for inversion and\\/or later phases. Ray-paths and travel times of later phases, as well as fastest arrivals, such as reflection, later refraction and P-SV converted waves, provide indispensable information for seismic crustal structure analyses. Although
R. Kubota; E. Nishiyama; K. Murase; J. Kasahara
Research of Rrogram Process Time Post-evaluation Grey Critical Path Algorithm Method Based on Grey Data Advantage Relationship
Program process time post-evaluation is a indeterminate grey information post-evaluation, the main aim of evaluation is test the validity of main event happened and the rationality of time-spending in the process of program implement. This paper researched the character of time process post-evaluation, clarified the data source of evaluation, constructed the grey critical paths (GCPM) basing on grey data advantage
Xuewen Tang; Sifeng Liu; Zhigeng Fang; Chuanmin Mi; Xiaogang Guo; Zhirui Qi
Path integral molecular dynamics method based on a pair density matrix approximation: An algorithm for distinguishable and identical particle systems
In this paper, the path integral molecular dynamics (PIMD) method has been extended to employ an efficient approximation of the path action referred to as the pair density matrix approximation. Configurations of the isomorphic classical systems were dynamically sampled by introducing fictitious momenta as in the PIMD based on the standard primitive approximation. The indistinguishability of the particles was handled by a pseudopotential of particle permutation that is an extension of our previous one [J. Chem. Phys. 112, 10 116 (2000)]. As a test of our methodology for Boltzmann statistics, calculations have been performed for liquid helium-4 at 4 K. We found that the PIMD with the pair density matrix approximation dramatically reduced the computational cost to obtain the structural as well as dynamical (using the centroid molecular dynamics approximation) properties at the same level of accuracy as that with the primitive approximation. With respect to the identical particles, we performed the calculation of a bosonic triatomic cluster. Unlike the primitive approximation, the pseudopotential scheme based on the pair density matrix approximation described well the bosonic correlation among the interacting atoms. Convergence with a small number of discretization of the path achieved by this approximation enables us to construct a method of avoiding the problem of the vanishing pseudopotential encountered in the calculations by the primitive approximation.
Miura, Shinichi; Okazaki, Susumu
Breast Contour Detection with Stable Paths
Breast cancer conservative treatment (BCCT), due to its proven oncological safety, is considered, when feasible, the gold standard of breast cancer treatment. However, aesthetic results are heterogeneous and difficult to evaluate in a standardized way, due to the lack of reproducibility of the subjective methods usually applied. The objective assessment methods, considered in the past as being less capable of evaluating all aspects of BCCT, are nowadays being preferred to overcome the drawbacks of the subjective evaluation. A computer-aided medical system was recently developed to objectively and automatically evaluate the aesthetic result of BCCT. In this system, the detection of the breast contour on the patient's digital photograph is a necessary step to extract the features subsequently used in the evaluation process. In this paper an algorithm based on the shortest path on a graph is proposed to detect automatically the breast contour. The proposed method extends an existing semi-automatic algorithm for the same purpose. A comprehensive comparison with manually-drawn contours reveals the strength of the proposed method.
Cardoso, Jaime S.; Sousa, Ricardo; Teixeira, Luís F.; Cardoso, M. J.
Structural phase transition path-following and stable phase scouting through a coupled DFT-BFB algorithm
This work formulates a new computational scheme to efficiently explore the configuration space of materials and to identify a material's stable equilibrium structures. This computational tool is obtained by coupling quantum-based density functional theory (DFT) calculations (employing periodic boundary conditions) with branch-following and bifurcation (BFB) techniques. BFB is used to map equilibrium paths (stable and unstable) on the DFT energy landscape as a function of the applied load and ultimately creates 'bifurcation maps' that identify the material's stable structures and connections between them, including: soft deformation directions, transition states, transformation mechanisms, etc. This new approach has been used to study structural transitions in Si and Fe under pressure loading. The results obtained so far indicate that the new DFT-BFB methodology has the potential to provide a significant new insight into the mechanisms that drive structural phase transitions in a wide range of technologically important materials.
Bhanu Ghosh, Dipta; Cococcioni, Matteo; Elliott, Ryan S.
Understanding structural phase transformations in solid-state materials is of great scientific and technological interest. These phenomena are governed by electronic degrees of freedom and thus, in principle, can be described with quantum mechanics alone. However, any realistic material has multiple length and time scales and access to these scales is a formidable task to deal with using quantum mechanics. On the contrary, for the continuum regime, empirical constitutive models have severe difficulties capturing material properties that ultimately arise from (sub-)atomic effects, and further, must be fit to experimental data. Thus, in order to obtain a predictive, complete understanding of a material subjected to different external loading parameters, the two regimes- atomistic and continuum-must be coupled. The present work formulates a coupled quantum-continuum model for scanning phase-space in order to determine the material's stable structure at any given pressure. This is accomplished by coupling quantumbased Density Functional Theory (DFT) calculations (employing periodic boundary conditions) with Branch- Following and Bifurcation (BFB) techniques. BFB is capable of mapping out equilibrium paths (stable and unstable) as a function of the applied pressure and ultimately creates "bifurcation maps" that identify the material's stable structures and connections between them, including: soft deformation directions, transition states, transformation mechanisms, etc.. This study shows that the coupled DFT-BFB methodology is capable of efficiently mapping out equilibrium paths. This includes the identification of stable and unstable pressure ranges and the identification of the deformation modes that first become soft-resulting in the structure's loss of stability. Example computations are provided for iron and silicon. The results obtained so far indicate that the new DFT-BFB methodology has the potential to provide a significant new insight on the mechanisms that drive structural phase transitions in a wide range of technologically important materials.
Ghosh, Dipta Bhanu; Cococcioni, Matteo; Elliott, Ryan S.
Planning multiple paths with evolutionary speciation
This paper demonstrates a new approach to multidimensional path planning that is based on multiresolution path representation, where explicit configuration space computation is not required, and incorporates an evolutionary algorithm for solving the multimodal optimization problem, generating multiple alternative paths simultaneously. The multiresolution path representation reduces the expected search length for the path-planning problem and accordingly reduces the overall computational
Cem Hocaoglu; Arthur C. Sanderson
Implementation of an algorithm based on the Runge-Kutta-Fehlberg technique and the potential energy as a reaction coordinate to locate intrinsic reaction paths.
The intrinsic reaction coordinate (IRC) curve is used widely as a representation of the Reaction Path and can be parameterized taking the potential energy as a reaction coordinate (Aguilar-Mogas et al., J Chem Phys 2008, 128, 104102). Taking this parameterization and its variational nature, an algorithm is proposed that permits to locate this type of curve joining two points from an arbitrary curve that joints the same initial and final points. The initial and final points are minima of the potential energy surface associated with the geometry of reactants and products of the reaction whose mechanism is under study. The arbitrary curves are moved toward the IRC curve by a Runge-Kutta-Fehlberg technique. This technique integrates a set of differential equations resulting from the minimization until value zero of the line integral over the Weierstrass E-function. The Weierstrass E-function is related with the second variation in the theory of calculus of variations. The algorithm has been proved in real chemical systems. PMID:20652993
Aguilar-Mogas, Antoni; Giménez, Xavier; Bofill, Josep Maria
Mobile transporter path planning
The use of a genetic algorithm (GA) for solving the mobile transporter path planning problem is investigated. The mobile transporter is a traveling robotic vehicle proposed for the space station which must be able to reach any point of the structure autonomously. Elements of the genetic algorithm are explored in both a theoretical and experimental sense. Specifically, double crossover, greedy crossover, and tournament selection techniques are examined. Additionally, the use of local optimization techniques working in concert with the GA are also explored. Recent developments in genetic algorithm theory are shown to be particularly effective in a path planning problem domain, though problem areas can be cited which require more research.
Optimal paths for a car that goes both forwards and backwards
The path taken by a car with a given minimum turning radius has a lower bound on its radius of curvature at each point, but the path has cusps if the car shifts into or out of reverse gear. What is the shortest such path a car can travel between two points if its starting and ending directions are specified?
J. A. Reeds; L. A. Shepp
Nonoptimal Component Placement, but Short Processing Paths, due to Long-Distance Projections in Neural Systems
It has been suggested that neural systems across several scales of organization show optimal component placement, in which any spatial rearrangement of the components would lead to an increase of total wiring. Using extensive connectivity datasets for diverse neural networks combined with spatial coordinates for network nodes, we applied an optimization algorithm to the network layouts, in order to search for wire-saving component rearrangements. We found that optimized component rearrangements could substantially reduce total wiring length in all tested neural networks. Specifically, total wiring among 95 primate (Macaque) cortical areas could be decreased by 32%, and wiring of neuronal networks in the nematode Caenorhabditis elegans could be reduced by 48% on the global level, and by 49% for neurons within frontal ganglia. Wiring length reductions were possible due to the existence of long-distance projections in neural networks. We explored the role of these projections by comparing the original networks with minimally rewired networks of the same size, which possessed only the shortest possible connections. In the minimally rewired networks, the number of processing steps along the shortest paths between components was significantly increased compared to the original networks. Additional benchmark comparisons also indicated that neural networks are more similar to network layouts that minimize the length of processing paths, rather than wiring length. These findings suggest that neural systems are not exclusively optimized for minimal global wiring, but for a variety of factors including the minimization of processing steps.
Kaiser, Marcus; Hilgetag, Claus C
Analysing Shortest Expected Delay Routing for Erlang Servers.
The queueing problem with a Poisson arrival stream and two identical, Erlang servers is analyzed for the queueing discipline based on shortest expected delay. This queueing problem may be represented as a random walk on the integer grid in the first quadr...
I. J. B. F. Adan J. Wessels
Algorithms for finding the weight-constrained k longest paths in a tree and the length-constrained k maximum-sum segments of a sequence
In this work, we obtain the following new results: - Given a tree T = (V;E) with a length function ' : E ! R and a weight function w : E !R, a positive integer k, and an interval (L;U), the Weight-Constrained k Longest Paths problem is to find the k longest paths among all paths in T with
Hsiao-fei Liu; Kun-mao Chao
Algorithmic Strategies in Combinatorial Chemistry
Combinatorial Chemistry is a powerful new technology in drug design and molecular recognition. It is a wet-laboratory methodology aimed at ``massively parallel'' screening of chemical compounds for the discovery of compounds that have a certain biological activity. The power of the method comes from the interaction between experimental design and computational modeling. Principles of ``rational'' drug design are used in the construction of combinatorial libraries to speed up the discovery of lead compounds with the desired biological activity. This paper presents algorithms, software development and computational complexity analysis for problems arising in the design of combinatorial libraries for drug discovery. The authors provide exact polynomial time algorithms and intractability results for several Inverse Problems-formulated as (chemical) graph reconstruction problems-related to the design of combinatorial libraries. These are the first rigorous algorithmic results in the literature. The authors also present results provided by the combinatorial chemistry software package OCOTILLO for combinatorial peptide design using real data libraries. The package provides exact solutions for general inverse problems based on shortest-path topological indices. The results are superior both in accuracy and computing time to the best software reports published in the literature. For 5-peptoid design, the computation is rigorously reduced to an exhaustive search of about 2% of the search space; the exact solutions are found in a few minutes.
Sampling diffusive transition paths.
The authors address the problem of sampling double-ended diffusive paths. The ensemble of paths is expressed using a symmetric version of the Onsager-Machlup formula, which only requires evaluation of the force field and which, upon direct time discretization, gives rise to a symmetric integrator that is accurate to second order. Efficiently sampling this ensemble requires avoiding the well-known stiffness problem associated with the sampling of infinitesimal Brownian increments of the path, as well as a different type of stiffness associated with the sampling of the coarse features of long paths. The fine-feature sampling stiffness is eliminated with the use of the fast sampling algorithm, and the coarse-feature sampling stiffness is avoided by introducing the sliding and sampling (S&S) algorithm. A key feature of the S&S algorithm is that it enables massively parallel computers to sample diffusive trajectories that are long in time. The authors use the algorithm to sample the transition path ensemble for the structural interconversion of the 38-atom Lennard-Jones cluster at low temperature. PMID:17444696
Miller, Thomas F; Predescu, Cristian
A Shortest Path Approach to the Multiple-Vehicle Routing Problem
Abstract We examine,a multiple-vehicle routing problem,that permits split pick-ups (mVRPSP). This problem,involves a fleet of trucks having identical capacity, multiple suppliers, and a single assembly plant. The fleet is responsible for moving parts from the suppliers to the assembly plant. The problem is to determine, for each truck, how many parts to pick up at each supplier to then transport
Yavuz A. Bozer
D-edge shortest-path problem for a Monge graph.
A complete edge-weighted directed graph on vertices 1,2,...,n that assigns cost c(i,j) to the edge (i,j) is called Monge if its edge costs form a Monge array, i.e., for all i < k and j < l, c(i, j)+c(k,l)(le) < c(i,l)+c(k,j). One reason Monge graphs are i...
W. W. Bein L. L. Larmore J. K. Park
Shortest-Path Network Analysis Is a Useful Approach toward Identifying Genetic Determinants of Longevity
Not Available Bibtex entry for this abstract Preferred format for this abstract (see Preferences) Find Similar Abstracts: Use: Authors Title Return: Query Results Return items starting with number Query Form Database: Astronomy Physics arXiv e-prints
J. R. Managbanag; Tarynn M. Witten; Danail Bonchev; Lindsay A. Fox; Mitsuhiro Tsuchiya; Brian K. Kennedy; Matt Kaeberlein; Ben Lehner
Dynamic Maintenance Versus Swapping: An Experimental Study on Shortest Paths Trees
Given a spanning tree T of a 2-edge connected, weighted graph G, a swap edge for a failing edge e in T is an edge é of G reconnecting\\u000a the two subtrees of T created bythe removal of e. A best swap edge is a swap edge enjoying the additional property of optimizing\\u000a the swap, with respect to a given
Guido Proietti
The shortest path from the surface to the nucleus: RBP-Jkappa\\/Su(H) transcription factor
Communication between cell surface receptors and nuclear transcription factors is of primary importance to multicellular organisms. Since there are numerous molecules involved in this process, their mutual interaction forms complex networks of informational regulation, which is still under extensive investigation. The RBP-J transcription factor interacts directly with the Notch receptor involved in cell lineage commitment, implicating the presence of a
Tasuku Honjo
Shortest paths on 3-D simple Lie groups with nonholonomic constraint
In this paper we study the Carnot-Caratheodory metrics on SU(2) ż S3, SO(3) and SL(2) induced by their Cartan decomposition and by the Killing form. Besides computing explicitly geodesics and conjugate loci, we compute the cut loci (globally) and we give the expression of the Carnot-Caratheodory distance as the inverse of an elementary function. For SU(2) the cut locus is
Ugo V. Boscain; Francesco Rossi
Approximate Bounds and Expressions for the Link Utilization of Shortest-Path Multicast Network Traffic
Multicast network traffic is information with one source node, but many destination nodes. Rather than setting up individual connections between the source node and each destination node, or broadcasting the information to the entire network, multicasting efficiently exploits link capacity by allowing the source node to transmit a small number of copies of the information to mutually-exclusive groups of destination
Borislav H. Simov; Srini B. Tridandapani; Michael S. Borella
Hardware\\/Software Integration for FPGA-based All-Pairs Shortest-Paths
Field-Programmable Gate Arrays (FPGAs) are be- ing employed in high performance computing systems owing to their potential to accelerate a wide variety of long-running routines. Parallel FPGA-based de- signs often yield a very high speedup. Applications us- ing these designs on reconfigurable supercomputers in- volve software on the system managing computation on the FPGA. To extract maximum performance from an
Uday Bondhugula; Ananth Devulapalli; James Dinan; Joseph Fernando; Pete Wyckoff; Eric Stahlberg; P. Sadayappan
From the Cover: Transitive functional annotation by shortest-path analysis of gene expression data
Current methods for the functional analysis of microarray gene expression data make the implicit assumption that genes with similar expression profiles have similar functions in cells. However, among genes involved in the same biological pathway, not all gene pairs show high expression similarity. Here, we propose that transitive expression similarity among genes can be used as an important attribute to
Hardware\\/Software Codesign for All-Pairs Shortest-Paths on a Reconfigurable Supercomputer
Rapid advances in VLSI technology have led to Field- Programmable Gate Arrays (FPGAs) being employed in High Performance Computing systems. Applications using FPGAs on reconfigurable supercomputers involve software on the system managing computation on the reconfigurable hardware. To extract maximum benefits from a parallel FPGA kernel at the application level, it becomes crucial to minimize data movement costs on the
A Flexible Reservation Algorithm for Advance Network Provisioning
Many scientific applications need support from a communication infrastructure that provides predictable performance, which requires effective algorithms for bandwidth reservations. Network reservation systems such as ESnet's OSCARS, establish guaranteed bandwidth of secure virtual circuits for a certain bandwidth and length of time. However, users currently cannot inquire about bandwidth availability, nor have alternative suggestions when reservation requests fail. In general, the number of reservation options is exponential with the number of nodes n, and current reservation commitments. We present a novel approach for path finding in time-dependent networks taking advantage of user-provided parameters of total volume and time constraints, which produces options for earliest completion and shortest duration. The theoretical complexity is only O(n2r2) in the worst-case, where r is the number of reservations in the desired time interval. We have implemented our algorithm and developed efficient methodologies for incorporation into network reservation frameworks. Performance measurements confirm the theoretical predictions.
Balman, Mehmet; Chaniotakis, Evangelos; Shoshani, Arie; Sim, Alex
An improved recursive decomposition algorithm for reliability evaluation of lifeline networks
The seismic reliability evaluation of lifeline networks has received considerable attention and been widely studied. In this paper, on the basis of an original recursive decomposition algorithm, an improved analytical approach to evaluate the seismic reliability of large lifeline systems is presented. The proposed algorithm takes the shortest path from the source to the sink of a network as decomposition policy. Using the Boolean laws of set operation and the probabilistic operation principal, a recursive decomposition process is constructed in which the disjoint minimal path set and the disjoint minimal cut set are simultaneously enumerated. As the result, a probabilistic inequality can be used to provide results that satisfy a prescribed error bound. During the decomposition process, different from the original recursive decomposition algorithm which only removes edges to simplify the network, the proposed algorithm simplifies the network by merging nodes into sources and removing edges. As a result, the proposed algorithm can obtain simpler networks. Moreover, for a network owning s-independent components in its component set, two network reduction techniques are introduced to speed up the proposed algorithm. A series of case studies, including an actual water distribution network and a large urban gas system, are calculated using the proposed algorithm. The results indicate that the proposed algorithm provides a useful probabilistic analysis method for the seismic reliability evaluation of lifeline networks.
Liu, Wei; Li, Jie
Integrated Flight Path Planning System and Flight Control System for Unmanned Helicopters
This paper focuses on the design of an integrated navigation and guidance system for unmanned helicopters. The integrated navigation system comprises two systems: the Flight Path Planning System (FPPS) and the Flight Control System (FCS). The FPPS finds the shortest flight path by the A-Star (A*) algorithm in an adaptive manner for different flight conditions, and the FPPS can add a forbidden zone to stop the unmanned helicopter from crossing over into dangerous areas. In this paper, the FPPS computation time is reduced by the multi-resolution scheme, and the flight path quality is improved by the path smoothing methods. Meanwhile, the FCS includes the fuzzy inference systems (FISs) based on the fuzzy logic. By using expert knowledge and experience to train the FIS, the controller can operate the unmanned helicopter without dynamic models. The integrated system of the FPPS and the FCS is aimed at providing navigation and guidance to the mission destination and it is implemented by coupling the flight simulation software, X-Plane, and the computing software, MATLAB. Simulations are performed and shown in real time three-dimensional animations. Finally, the integrated system is demonstrated to work successfully in controlling the unmanned helicopter to operate in various terrains of a digital elevation model (DEM).
Jan, Shau Shiun; Lin, Yu Hsiang
Integrated flight path planning system and flight control system for unmanned helicopters.
This paper focuses on the design of an integrated navigation and guidance system for unmanned helicopters. The integrated navigation system comprises two systems: the Flight Path Planning System (FPPS) and the Flight Control System (FCS). The FPPS finds the shortest flight path by the A-Star (A*) algorithm in an adaptive manner for different flight conditions, and the FPPS can add a forbidden zone to stop the unmanned helicopter from crossing over into dangerous areas. In this paper, the FPPS computation time is reduced by the multi-resolution scheme, and the flight path quality is improved by the path smoothing methods. Meanwhile, the FCS includes the fuzzy inference systems (FISs) based on the fuzzy logic. By using expert knowledge and experience to train the FIS, the controller can operate the unmanned helicopter without dynamic models. The integrated system of the FPPS and the FCS is aimed at providing navigation and guidance to the mission destination and it is implemented by coupling the flight simulation software, X-Plane, and the computing software, MATLAB. Simulations are performed and shown in real time three-dimensional animations. Finally, the integrated system is demonstrated to work successfully in controlling the unmanned helicopter to operate in various terrains of a digital elevation model (DEM). PMID:22164029
Planning Monotone Paths to Visit a Set of Obstacles.
Computing a shortest collision-free path connecting points s and t that visits a given set of obstacles in two dimensions is like the travelling salesman problem and is NP-hard. We consider a restricted version of the above problem called the s-t-monotone...
L. P. Gewali
Path planning for virtual bronchoscopy.
We have developed an automated path planning method, which enables virtual bronchoscopic 3D multidetector computed tomography (MDCT) image analysis and follow on image-guided bronchoscopy. The method fundamentals are novel combination of distance transformation and snake-based models. The computation time of our algorithm is faster than similar works and there were no missing or false branches in the final path of airways. The planned path is suitable for quantitative airway analysis and smooth virtual navigation. PMID:17946384
Negahdar, Mohamadreza; Ahmadian, Alireza; Navab, Nassir; Firouznia, Kavous
Sorting, Minimal Feedback Sets and Hamilton Paths in Tournaments.
The authors present a general method for translating sorting by comparisons algorithms to algorithms that compute a Hamilton path in a tournament. The translation is based on the relation between minimal feedback sets and Hamilton paths in tournaments. Th...
A. Bar-Noy J. Naor
Curved paths in raptor flight: Deterministic models.
Two deterministic models for flight of Peregrine Falcons and possibly other raptors as they approach their prey are examined mathematically. Both models make two assumptions. The first, applicable to both models, is that the angle of sight between falcon and prey is constant, consistent with observations that the falcon keeps its head straight during flight and keeps on course by use of the deep foveal region in its eye which allows maximum acuity at an angle of sight of about 45 degrees . The second assumption for the first model (conical spiral), is that the initial direction of flight determines the overall path. For the second model (flight constrained to a tilted plane), a parameter that fixes the orientation of the plane is required. A variational calculation also shows that the tilted plane flight path is the shortest total path, and, consequently, the conical spiral is another shortest total path. Numerical calculations indicate that the flight paths for the two models are very similar for the experimental conditions under which observations have been made. However, the angles of flight and bank differ significantly. More observations are needed to investigate the applicability of the two models. PMID:16757000
Lorimer, John W
Computational experience with the octahedral algorithm and related results. Technical Report SOL 83-8
This paper investigates the computational efficiency of the octahedral algorithm of Wright. The algorithm avoids a subdivision of the full product space R/sup n/ x (0, 1); in particular, only 2n artificial vertices are required. The algorithm can be interpreted as a variable dimension algorithm in which simplices in R/sup n/ of varying dimension are traversed. There are 2/sup n/ directions (rays) where efficient one-dimensional pivots are permitted. These and other features make the octahedral algorithm a promising new method for computing fixed points. The algorithm can be interpreted as dual to the cubical algorithm of Van der Laan and Talman (1981), see Wright (1981). Their cubical algorithm which has 2n-rays is based on C/sup n/, the n-dimensional unit cube, which is dual to O/sup n/. A concise description is presented of the octahedral algorithm and the replacement (pivot) rules which are necessary to implement the algorithm are given. Computational results are given and shortest paths through the octahedral subdivision are derived.
Broadie, M.N.
Tornado Paths
This website catalogs all the tornado paths in the United States since 1950. The tornado path data is overlaid onto a Google Maps base for easy browsing and manipulation of the map view. Clicking on individual tornados provides the user with information such as its Fujita rating, the amount of damage caused by the tornado, the size of the path that the tornado made, and the length of time the tornado was on the ground.
Samson, Perry; Michigan, University O.
A star recognition method based on the Adaptive Ant Colony algorithm for star sensors.
A new star recognition method based on the Adaptive Ant Colony (AAC) algorithm has been developed to increase the star recognition speed and success rate for star sensors. This method draws circles, with the center of each one being a bright star point and the radius being a special angular distance, and uses the parallel processing ability of the AAC algorithm to calculate the angular distance of any pair of star points in the circle. The angular distance of two star points in the circle is solved as the path of the AAC algorithm, and the path optimization feature of the AAC is employed to search for the optimal (shortest) path in the circle. This optimal path is used to recognize the stellar map and enhance the recognition success rate and speed. The experimental results show that when the position error is about 50?, the identification success rate of this method is 98% while the Delaunay identification method is only 94%. The identification time of this method is up to 50 ms. PMID:22294908
Quan, Wei; Fang, Jiancheng
A Star Recognition Method Based on the Adaptive Ant Colony Algorithm for Star Sensors
A new star recognition method based on the Adaptive Ant Colony (AAC) algorithm has been developed to increase the star recognition speed and success rate for star sensors. This method draws circles, with the center of each one being a bright star point and the radius being a special angular distance, and uses the parallel processing ability of the AAC algorithm to calculate the angular distance of any pair of star points in the circle. The angular distance of two star points in the circle is solved as the path of the AAC algorithm, and the path optimization feature of the AAC is employed to search for the optimal (shortest) path in the circle. This optimal path is used to recognize the stellar map and enhance the recognition success rate and speed. The experimental results show that when the position error is about 50?, the identification success rate of this method is 98% while the Delaunay identification method is only 94%. The identification time of this method is up to 50 ms.
Network approaches to two-dimensional phase unwrapping: intractability and two new algorithms.
Two-dimensional (2-D) phase unwrapping, that is, deducing unambiguous phase values from a 2-D array of values known only modulo 2pi, is a key step in interpreting data acquired with synthetic aperture radar interferometry. Noting the recent network formulation of the phase unwrapping problem, we apply here some well-established ideas of network theory to formalize the problem, analyze its complexity, and derive algorithms for its solution. It has been suggested that the objective of phase unwrapping should be to minimize the total number of places where unwrapped and wrapped phase gradients differ. Here we use network constructions to show that this so-called minimum L0-norm problem is NP-hard, or one that complexity theory suggests is impossible for efficient algorithms to solve exactly. Therefore we must instead find approximate solutions; we present two new algorithms for doing so. The first uses the network ideas of shortest paths and spanning trees to improve on the Goldstein et al. residue-cut algorithm [Radio Sci. 23, 713 (1988)]. Our improved algorithm is very fast, provides complete coverage, and allows user-defined weights. With our second algorithm, we extend the ideas of linear network flow problems to the nonlinear L0 case. This algorithm yields excellent approximations to the minimum L0 norm. Using interferometric data, we demonstrate that our algorithms are highly competitive with other existing algorithms in speed and accuracy, outperforming them in the cases presented here. PMID:10708020
Chen, C W; Zebker, H A
Path ensembles and path sampling in nonequilibrium stochastic systems.
Markovian models based on the stochastic master equation are often encountered in single molecule dynamics, reaction networks, and nonequilibrium problems in chemistry, physics, and biology. An efficient and convenient method to simulate these systems is the kinetic Monte Carlo algorithm which generates continuous-time stochastic trajectories. We discuss an alternative simulation method based on sampling of stochastic paths. Utilizing known probabilities of stochastic paths, it is possible to apply Metropolis Monte Carlo in path space to generate a desired ensemble of stochastic paths. The method is a generalization of the path sampling idea to stochastic dynamics, and is especially suited for the analysis of rare paths which are not often produced in the standard kinetic Monte Carlo procedure. Two generic examples are presented to illustrate the methodology. PMID:17867733
Harland, Ben; Sun, Sean X
Removing False Paths from Combinational Modules 1
The existence of false paths complicates the task of accurate tim- ing analysis significantly. A technique to remove false paths from a combinational circuit without degrading its performance h as a prac- tical value since topological timing analysis is then good e nough to estimate the performance of false-path-free circuits accu rately. One can think of the KMS algorithm (1)
Yuji Kukimoto; Robert K. Brayton
SCTP Performance Issue on Path Delay Differential
This paper studies the effect of path delay on SCTP performance. It focuses on the SCTP fast retransmit algorithm and demonstrates that the performance in the current retransmission strategy will degrade acutely when the secondary path delay is less than the primary path delay at a certain level. The performance degradation is due to the disordered SACKs and constant congestion
Yuansong Qiao; Enda Fallon; Liam Murphy; John Murphy; Austin Hanley; Xiaosong Zhu; Adrian Matthews; Eoghan Conway; Gregory Hayes
At-Least Version of the Generalized Minimum Spanning Tree Problem: Optimization Through Ant Colony System and Genetic Algorithms
The At-Least version of the Generalized Minimum Spanning Tree Problem (L-GMST) is a problem in which the optimal solution connects all defined clusters of nodes in a given network at a minimum cost. The L-GMST is NPHard; therefore, metaheuristic algorithms have been used to find reasonable solutions to the problem as opposed to computationally feasible exact algorithms, which many believe do not exist for such a problem. One such metaheuristic uses a swarm-intelligent Ant Colony System (ACS) algorithm, in which agents converge on a solution through the weighing of local heuristics, such as the shortest available path and the number of agents that recently used a given path. However, in a network using a solution derived from the ACS algorithm, some nodes may move around to different clusters and cause small changes in the network makeup. Rerunning the algorithm from the start would be somewhat inefficient due to the significance of the changes, so a genetic algorithm based on the top few solutions found in the ACS algorithm is proposed to quickly and efficiently adapt the network to these small changes.
Janich, Karl W.
Parallel Shortest Lattice Vector Enumeration on Graphics Cards
In this paper we present an algorithm for parallel exhaustive search for short vectors in lattices. This algorithm can be applied to a wide range of parallel computing systems. To illustrate the algorithm, it was implemented on graphics cards using CUDA, a programming frame- work for NVIDIA graphics cards. We gain large speedups compared to previous serial CPU implementations. Our
Jens Hermans; Michael Schneider; Johannes Buchmann; Frederik Vercauteren; Bart Preneel
Effectiveness of the statistical potential in the description of fermions in a worm-algorithm path-integral Monte Carlo simulation of 3He atoms placed on a 4He layer adsorbed on graphite.
We demonstrate the effectiveness of a statistical potential (SP) in the description of fermions in a worm-algorithm path-integral Monte Carlo simulation of a few 3He atoms floating on a 4He layer adsorbed on graphite. The SP in this work yields successful results, as manifested by the clusterization of 3He, and by the observation that the 3He atoms float on the surface of 4He. We display the positions of the particles in 3D coordinate space, which reveal clusterization of the 3He component. The correlation functions are also presented, which give further evidence for the clusterization. PMID:22400696
Ghassib, Humam B; Sakhel, Asaad R; Obeidat, Omar; Al-Oqali, Amer; Sakhel, Roger R
EPA Science Inventory
Open-path Fourier transform infrared (OP/FTIR) spectrometry was used to measure the concentrations of ammonia, methane, and other atmospheric gases at an integrated swine production facility. The concentration-pathlength products of the target gases at this site often exceeded th...
Quantum Path Interferences in High-Order Harmonic Generation
We have investigated the intensity dependence of high-order harmonic generation in argon when the two shortest quantum paths contribute to the harmonic emission. For the first time to our knowledge, experimental conditions were found to clearly observe interference between these two quantum paths that are in excellent agreement with theoretical predictions. This result is a first step towards the direct experimental characterization of the full single-atom dipole moment and demonstrates an unprecedented accuracy of quantum path control on an attosecond time scale.
Zaier, A.; Holler, M.; Guandalini, A.; Schapper, F.; Biegert, J.; Gallmann, L.; Keller, U.; Wyatt, A. S.; Monmayrant, A.; Walmsley, I. A.; Cormier, E.; Auguste, T.; Caumes, J. P.; Salieres, P. [Physics Department, ETH Zurich, CH-8093 Zurich (Switzerland); Clarendon Laboratory, Parks Road, Oxford OX1 3PU (United Kingdom); CELIA, CNRS-CEA-Universite Bordeaux1, 351 cours de la liberation, 33405 Talence (France); Service des Photons, Atomes et Molecules, CEA-Saclay, 91191 Gif-sur-Yvette (France)
Path Finder
Finding certain files on a computer can be an onerous chore from time to time, and Path Finder is a good solution for anyone who's been bedeviled by such a task. The application includes a dual pane browser, cut and paste support, and a website that includes an interactive tour through its other features. This version of Path Finder is compatible with systems running Mac OS X 10.5 and newer. Also, this is a 30-day free trial version, and a full paid license is required after that point.
Path Planning by Negotiation for Decentralized Agents
This paper presents a real-time path-planning algorithm for decentralized agents, which provides guaranteed collision-free paths for the agents towards their desired destinations. The algorithm is run locally on the agents, which can exchange information using wireless communication. The algorithm is robust with respect to arbitrary delays in the wireless traffic, possible sources being transmission time, error correction, and others. Agents
Oliver Purwin; R. D'Andrea
Construction of Optimal-Path Maps for Homogeneous-Cost-Region Path-Planning Problems.
Fast path-planning algorithms are needed for autonomous vehicles and tactical terrain-analysis tools. We explore a new approach using 'optimal-path maps', that give the best path to a goal point from any given start point in cross-country two-dimensional ...
R. S. Alexander
Disk scheduling algorithms based on rotational position
When sufficient processor power is available, disk scheduling based on rotational position as well as disk arm position is shown to provide improved performance. A taxonomy of algorithms based on Shortest Access Time First (SATF) have been developed, and several of them have been explored through simulations. The access-time based algorithms match or outperform all the seek-time ones we studied.
D. Jacobsen; J. Wilkes
Applications of Path Compression on Balanced Trees
Several fast algorithms are presented for computing functions defined on paths in trees under various assumpuons. The algorithms are based on tree mampulatton methods first used to efficiently represent equivalence relations. The algorithms have O((m + n)a(m + n, n)) running tunes, where m and n are measures of the problem size and a Is a functional reverse of Ackermann's
Term Paths
Students follow several pathways using anatomical directions on a simulated "body" produced from a copy of a school building's fire evacuation plan. The main hallways are designated as major blood vessels and the various areas of the school, the head, chest, abdomen, etc. Students complete several pathways using anatomical terms as directions. For example, one of my paths begins, "Ex- ot-, ad- superior, ecto- derm-, peri-frontal, circum- rhino-, " which loosely means, exit the ear, go to the superior region, outside the skin, around the frontal region, around the nose. At the end of each path I leave a clue that lets me know the students actually made it. The combined clues form a sentence.
Cynthia Ann Radle (McCullough High School REV)
Path Clearance
In military scenarios, agents (i.e., troops of soldiers, convoys, and unmanned vehicles) may often have to traverse environments with only a limited intelligence about the locations of adversaries. We study a particular instance of this problem that we refer to as path clearance problem.This article presents a survey of our work on scalable and suitable for real-time use approaches to
Maxim Likhachev; Anthony Stentz
Feynman path integrals in the young double-slit experiment
An estimate for the value of the nonlinear interference term in the Young double-slit experiment is found using the Feynman path-integral method. In our time-dependent calculation the usual interference term becomes multiplied by 1+e withe proportional to cos(2m? L\\/ hT), where ? is the distance between the two slits (holes) andL is the length of the shortest trajectory of electrons
H. Yabuki
Feynman Path Integrals in the Young Double-Slit Experiment
An estimate for the value of the nonlinear interference term in the Young double-slit experiment is found using the Feynman path-integral method. In our time-dependent calculation the usual interference term becomes multiplied by 1+ e with e proportional to cos(2 m? L/ ? T), where ? is the distance between the two slits (holes) and L is the length of the shortest trajectory of electrons between the source and the observation point.
Yabuki, H.
An estimate for the value of the nonlinear interference term in the Young double-slit experiment is found using the Feynman path-integral method. In our time-dependent calculation the usual interference term becomes multiplied by 1 + e with e proportional to cos(2mlambdaL//eta/T), where lambda is the distance between the two slits (holes) and L is the length of the shortest trajectory of electrons between the source and the observation point.
Path Planning by Querying Persistent Stores of Trajectory Segments.
We introduce an algorithm for path planning (long duration) paths of dynamical systems, given a persistent object store containing suitable collections of short duration trajectory segments. We also describe experimental results from a proof-of-concept im...
R. L. Grossman S. Mehta X. Qin
Sweep Algorithm in Vehicle Routing Problem For Public Transport
This paper investigates the capability of Sweep Algorithm in solving the vehicle routing problem for public transport The Sweep Algorithm is firstly introduced as a method to search shortest route in the vehicle routing problem. In order to evaluate the result of the algorithm, current routes profile of a public transport is presented. An application is constructed based on the
Routing and scheduling of hazardous materials shipments: algorithmic approaches to managing spent nuclear fuel transport
Much controversy surrounds government regulation of routing and scheduling of Hazardous Materials Transportation (HMT). Increases in operating costs must be balanced against expected benefits from local HMT bans and curfews when promulgating or preempting HMT regulations. Algorithmic approaches for evaluating HMT routing and scheduling regulatory policy are described. A review of current US HMT regulatory policy is presented to provide a context for the analysis. Next, a multiobjective shortest path algorithm to find the set of efficient routes under conflicting objectives is presented. This algorithm generates all efficient routes under any partial ordering in a single pass through the network. Also, scheduling algorithms are presented to estimate the travel time delay due to HMT curfews along a route. Algorithms are presented assuming either deterministic or stochastic travel times between curfew cities and also possible rerouting to avoid such cities. These algorithms are applied to the case study of US highway transport of spent nuclear fuel from reactors to permanent repositories. Two data sets were used. One data set included the US Interstate Highway System (IHS) network with reactor locations, possible repository sites, and 150 heavily populated areas (HPAs). The other data set contained estimates of the population residing with 0.5 miles of the IHS and the Eastern US. Curfew delay is dramatically reduced by optimally scheduling departure times unless inter-HPA travel times are highly uncertain. Rerouting shipments to avoid HPAs is a less efficient approach to reducing delay.
Cox, R.G.
Path tracking in underwater vehicle navigation - on-line evaluation of guidance path errors via vision sensor
In this paper a vision-based algorithm for on-line estimation of position control errors in a guidance system for path tracking is presented. The algorithm uses techniques of pattern recognition, however with a high degree of morphological simplifications. The algorithm detects the path line stretch which is displayed in the actual frame, and estimates the slope of the line and its
Mario Alberto Jordan; Carlos Enrique Berger; Jorge Luis Bustamante; Santiago Hansen
Tool-path planning for direction-parallel area milling
Presented in the paper is a tool-path planning algorithm for direction-parallel area milling consisting of three modules: (1) finding the optimal inclination; (2) calculating and storing tool-path elements; and (3) tool-path linking. For the optimal inclination, we suggest an algorithm that selects an inclination by reflecting the shape of the machining area as well as the tool-path interval. We make
Sang C. Park; Byoung Kyu Choi
Maintaining Incremental Optimality When Building Shortest Euclidean Tours.
Reported upon are experimental runs of an algorithm designed to incremental optimality when building tours for the Euclidean traveling salesman problem. Unlike the Lin-Kernighan edge eschange or Padberg-Rinaldi branch-and-cut techniques which begin with s...
T. M. Cronin
Path planning using a tangent graph for mobile robots among polygonal and curved obstacles
This article proposes a tangent graph for path planning of mobile robots among obstacles with a general boundary. The tangent graph is defined on the basis of the locally shortest path. It has the same data structure as the visibility graph, but its nodes represent common tangent points on obstacle boundaries, and its edges correspond to collision-free common tangents between the boundaries and convex boundary segments between the tangent points. The tangent graph requires O(K[sup 2]) memory, where K denotes the total number of convex segments of the obstacle boundaries. The tangent graph includes all locally shortest paths and is capable of coping with path planning not only among polygonal obstacles but also among curved obstacles.
Liu, Yun-Hui; Arimoto, Suguru (Univ. of Tokyo (Japan))
This paper deals with a characterization of the shortest paths for lateral navigation of an autonomous underactuated airship taking into account its dynamics and actuator limitations. The initial and terminal positions are given. We would like to specify the control forces that steer the unmanned aerial vehicle to the given terminal position requiring the minimal time for lateral navigation. The
Salim Hima; Yasmina Bestaoui
Going against the flow: finding the optimal path
We consider the problem of finding the optimum path of a boat traversing a straight in a current. The path of the shortest time is found using the calculus of variations with the constraint that the boat must land directly opposite to its starting point. We compare the optimal trajectory with that where the boat's local orientation is always directed to the arrival point. When analytical solutions cannot be found we use numerical methods. The level of the exposition is suitable for advanced undergraduate students, graduate students and general physicists.
Talbot, Julian
Path Planning Control.
Viewgraphs on path planning control are presented. Topics covered include: model based path planning; sensor based path planning; hybrid path planning; proximity sensor array; and applications for fuzzy logic.
M. Mcroberts
Path planning control
Mcroberts, Malcolm
Global Path Planning Approach for Redundant Manipulators.
A new approach for global path planning of redundant manipulators is proposed. It poses the path planning problem as a finite time nonlinear control problem. The solution is found by a Newton-Raphson type algorithm. This technique is capable of handling v...
S. Seereeram J. Wen
UAV Path Planning for Passive Emitter Localization
A path planning algorithm is presented for uninhabited aerial vehicles (UAVs) trying to geolocate an emitter using passive payload sensors. The objective is to generate a sequence of waypoints for each vehicle that minimizes localization uncertainty. The path planning problem is cast as a nonlinear programming problem using an approximation of the Fisher information matrix (FIM) and solved at successive
Kutluyil Dogancay
Efficient Algorithms for Average Completion Time Scheduling
We analyze the competitive ratio of algorithms for minimizing (weighted) average completion time on identical parallel machines and prove that the well-known shortest remaining processing time algorithm (SRPT) is 5/4-competitive w.r.t. the average completion time objective. For weighted completion times we give a deterministic algorithm with competitive ratio 1.791 + o(m). This ratio holds for preemptive and non-preemptive scheduling.
Sitters, René
Path planning by querying persistent stores of trajectory segments
We introduce an algorithm for path planning (long duration) paths of dynamical systems, given a persistent object store containing suitable collections of short duration trajectory segments. We also describe experimental results from a proof-of-concept implementation of the algorithm. The basic idea is to interpret a path planning algorithm as a suitable query on a persistent object store consisting of short duration trajectory segments. The query returns a concatenation of short duration trajectory segments which is close to the desired path. The needed short duration segments are computed by using a divide and conquer algorithm to break up the original path into shorter paths; each shorter path is then matched to a nearby trajectory segment which is part of the persistent object store by using a suitable index function.
Grossman, Robert L.; Mehta, S.; Qin, Xiao
Route choices of transport bicyclists: a comparison of actually used and shortest routes
Background Despite evidence that environmental features are related to physical activity, the association between the built environment and bicycling for transportation remains a poorly investigated subject. The aim of the study was to improve our understanding of the environmental determinants of bicycling as a means of transportation in urban European settings by comparing the spatial differences between the routes actually used by bicyclists and the shortest possible routes. Methods In the present study we examined differences in the currently used and the shortest possible bicycling routes, with respect to distance, type of street, and environmental characteristics, in the city of Graz, Austria. The objective measurement methods of a Global Positioning System (GPS) and a Geographic Information System (GIS) were used. Results Bicycling routes actually used were significantly longer than the shortest possible routes. Furthermore, the following attributes were also significantly different between the used route compared to the shortest possible route: Bicyclists often used bicycle lanes and pathways, flat and green areas, and they rarely used main roads and crossings. Conclusion The results of the study support our hypothesis that bicyclists prefer bicycle pathways and lanes instead of the shortest possible routes. This underlines the importance of a well-developed bicycling infrastructure in urban communities.
A Comparison of Two Path Planners for Planetary Rovers
The paper presents two path planners suitable for planetary rovers. The first is based on fuzzy description of the terrain, and genetic algorithm to find a traversable path in a rugged terrain. The second planner uses a global optimization method with a cost function that is the path distance divided by the velocity limit obtained from the consideration of the rover static and dynamic stability. A description of both methods is provided, and the results of paths produced are given which show the effectiveness of the path planners in finding near optimal paths. The features of the methods and their suitability and application for rover path planning are compared
Tarokh, M.; Shiller, Z.; Hayati, S.
Data-Oriented Algorithm for Route Choice Set Generation in a Metropolitan Area with Mobile Phone GPS Data
Nowadays, for the estimation of traffic demand or people flow, modelling route choice activity in road networks is an important task and many algorithms have been developed to generate route choice sets. However, developing an algorithm based on a small amount of data that can be applied generally within a metropolitan area is difficult. This is because the characteristics of road networks vary widely. On the other hand, recently, the collection of people movement data has lately become much easier, especially through mobile phones. Lately, most mobile phones include GPS functionality. Given this background, we propose a data-oriented algorithm to generate route choice sets using mobile phone GPS data. GPS data contain a number of measurement errors; hence, they must be adjusted to account for these errors before use in advanced people movement analysis. However, this is time-consuming and expensive, because an enormous amount of daily data can be obtained. Hence, the objective of this study is to develop an algorithm that can easily manage GPS data. Specifically, at first movement data from all GPS data are selected by calculating the speed. Next, the nearest roads in the road network are selected from the GPS location and count such data for each road. Then An algorithm based on the GSP (Gateway Shortest Path) algorithm is proposed, which searches the shortest path through a given gateway. In the proposed algorithm, the road for which the utilization volume calculated by GPS data is large is selected as the gateway. Thus, route choice sets that are based on trends in real GPS data are generated. To evaluate the proposed method, GPS data from 0.7 million people a year in Japan and DRM (Digital Road Map) as the road network are used. DRM is one of the most detailed road networks in Japan. Route choice sets using the proposed algorithm are generated and the cover rate of the utilization volume of each road under evaluation is calculated. As a result, the proposed route generation algorithm and GPS data cleaning process work well and a huge variety of routes that have high potential to be used in the real world can be generated.
Nakamura, T.; Sekimoto, Y.; Usui, T.; Shibasaki, R.
A Procedure for Computing the K Best Solutions to Discrete Optimization Problems and Its Application to the Shortest Path Problem
A general procedure is presented for computing the best, 2nd best,..., Kth best solutions to a given discrete optimization problem. If the number of computational steps required to find an optimal solution to a problem with n(0, 1) variables is c(n), then the amount of computation required to obtain the if best solutions is O(Knc<\\/sub>(n)). The procedure specializes to published
Eugene L. Lawler
Optimizing public transit quality and system access: the multiple-route, maximal covering\\/shortest-path problem
Public transit service is a promising travel mode because of its potential to address urban sustainability. However, current ridership of public transit is very low in most urban regions -- particularly those in the United States. Low transit ridership can be attributed to many factors, among which poor service quality is key. Transit service quality may potentially be improved by
Changshan Wu; Alan T Murray
A hybrid genetic algorithm for the weight setting problem in OSPF\\/ISIS routing
Intradomain traffic engineering aims to make more effi- cient use of network resources within an autonomous system. Interior Gateway Protocols such as OSPF (Open Shortest Path First) and IS-IS (Intermediate System- Intermediate System) are commonly used to select the paths along which traffic is routed within an autonomous system. These routing protocols direct traffic based on link weights assigned by
Luciana S. Buriol; Mauricio G. C. Resende; Celso C. Ribeiro; Mikkel Thorup
A Genetic Algorithm for the Weight Setting Problem in OSPF Routing
With the growth of the Internet, Internet Service Providers (ISPs) try to meet the increasing trac demand with new technology and improved utilization of existing resources. Routing of data packets can aect network utilization. Packets are sent along network paths from source to destination following a protocol. Open Shortest Path First (OSPF) is the most commonly used intra-domain Internet routing
M. Ericsson; Mauricio G. C. Resende; Panos M. Pardalos
Design of an Intelligent Route Planning System Using an Enhanced A*-search Algorithm
Traffic congestion has become a major problem in many countries. One of the main causes is the failure to manage a journey. Vehicles tend to choose the shortest paths which ended up congesting a certain area. If a journey is well managed, using alternative paths may lead to the same destination in a shorter period of time. Therefore, with the
Wong Poh Lee; Mohd Azam Osman; Maziani Sabudin
Environmental Measurements Path Planner (EMPath) User's Manual.
A suite of sensors in an oceanographic area of interest may be optimized with the use of a Genetic Algorithm. The purpose of the Environmental Measurements Path Planner (EMPath) is to use and execute a genetic algorithm to generate optimal search plans fo...
G. Peggion K. D. Heaney L. F. Smedstad R. H. Stroop R. L. Campbell
Metabolic Flux-Based Modularity using Shortest Retroactive distances
Background Graph-based modularity analysis has emerged as an important tool to study the functional organization of biological networks. However, few methods are available to study state-dependent changes in network modularity using biological activity data. We develop a weighting scheme, based on metabolic flux data, to adjust the interaction distances in a reaction-centric graph model of a metabolic network. The weighting scheme was combined with a hierarchical module assignment algorithm featuring the preservation of metabolic cycles to examine the effects of cellular differentiation and enzyme inhibitions on the functional organization of adipocyte metabolism. Results Our analysis found that the differences between various metabolic states primarily involved the assignment of two specific reactions in fatty acid synthesis and glycerogenesis. Our analysis also identified cyclical interactions between reactions that are robust with respect to metabolic state, suggesting possible co-regulation. Comparisons based on cyclical interaction distances between reaction pairs suggest that the modular organization of adipocyte metabolism is stable with respect to the inhibition of an enzyme, whereas a major physiological change such as cellular differentiation leads to a more substantial reorganization. Conclusion Taken together, our results support the notion that network modularity is influenced by both the connectivity of the network's components as well as the relative engagements of the connections.
Path Set Selection in Mobile Ad Hoc Networks
Topological changes in mobile ad hoc networks frequently render routing paths unusable. Such recurrent path failures have detrimental effects on the network ability to support QoS-driven services. A promising technique for addressing this problem is to use multiple redundant paths between the source and the destination. However while multipath routing algorithms can tolerate network failures well their failure resilience only
Panagiotis Papadimitratos; E. G. Sirer; Z. J. Haas
Loop Algorithm
The loop algorithm for the world-line quantum Monte Carlo method on quantum lattice models is presented. After introducing the path integral representation that maps a quantum model to a classical one, we describe the continuous imaginary time limit, cluster algorithm, and the rejection free scheme, which are the major improvements on the quantum Monte Carlo technique during the last decades. By means of the loop algorithm, one can simulate various unfrustrated quantum lattice models of millions of sites at extremely low temperatures with absolute accuracy, being free from the critical and fine-mesh slowing down and the Suzuki-Trotter discretization error. We also discuss some technical aspects of the algorithm such as effective implementation and parallelization.
Todo, Synge
Analysis of a Bloom Filter Algorithm via the Supermarket Model
This paper deals with the problem of identifying elephants in the Internet Traffic. The aim is to analyze a new adaptive algorithm based on a Bloom Filter. This algorithm uses a so-called min-rule which can be described as in the supermarket model. This model consists of joining the shortest queue among d queues selected at random in a large number
Yousra Chabchoub; Christine Fricker; Hanene Mohamed
Maximum Flux Transition Paths of Conformational Change.
Given two metastable states A and B of a biomolecular system, the problem is to calculate the likely paths of the transition from A to B. Such a calculation is more informative and more manageable if done for a reduced set of collective variables chosen so that paths cluster in collective variable space. The computational task becomes that of computing the "center" of such a cluster. A good way to define the center employs the concept of a committor, whose value at a point in collective variable space is the probability that a trajectory at that point will reach B before A. The committor "foliates" the transition region into a set of isocommittors. The maximum flux transition path is defined as a path that crosses each isocommittor at a point which (locally) has the highest crossing rate of distinct reactive trajectories. This path is based on the same principle as the minimum resistance path of Berkowitz et al (1983), but it has two advantages: (i) the path is invariant with respect to a change of coordinates in collective variable space and (ii) the differential equations that define the path are simpler. It is argued that such a path is nearer to an ideal path than others that have been proposed with the possible exception of the finite-temperature string method path. To make the calculation tractable, three approximations are introduced, yielding a path that is the solution of a nonsingular two-point boundary-value problem. For such a problem, one can construct a simple and robust algorithm. One such algorithm and its performance is discussed. PMID:20890401
Zhao, Ruijun; Shen, Juanfang; Skeel, Robert D
The Length of the Shortest Telomere as the Major Determinant of the Onset of Replicative Senescence
The absence of telomerase in many eukaryotes leads to the gradual shortening of telomeres, causing replicative senescence. In humans, this proliferation barrier constitutes a tumor suppressor mechanism and may be involved in cellular aging. Yet the heterogeneity of the senescence phenotype has hindered the understanding of its onset. Here we investigated the regulation of telomere length and its control of senescence heterogeneity. Because the length of the shortest telomeres can potentially regulate cell fate, we focus on their dynamics in Saccharomyces cerevisiae. We developed a stochastic model of telomere dynamics built on the protein-counting model, where an increasing number of protein-bound telomeric repeats shift telomeres into a nonextendable state by telomerase. Using numerical simulations, we found that the length of the shortest telomere is well separated from the length of the others, suggesting a prominent role in triggering senescence. We evaluated this possibility using classical genetic analyses of tetrads, combined with a quantitative and sensitive assay for senescence. In contrast to mitosis of telomerase-negative cells, which produces two cells with identical senescence onset, meiosis is able to segregate a determinant of senescence onset among the telomerase-negative spores. The frequency of such segregation is in accordance with this determinant being the length of the shortest telomere. Taken together, our results substantiate the length of the shortest telomere as being the key genetic marker determining senescence onset in S. cerevisiae.
Xu, Zhou; Duc, Khanh Dao; Holcman, David; Teixeira, Maria Teresa
A mathematical model is proposed to describe how vacant and occupied taxis will cruise in a road network to search for customers and provide transportation services. The model assumes that a taxi driver, once having picked up a customer, will move to the customer's destination by the shortest path; and that a taxi driver, once having dropped a customer, will
S C Wong; Hai Yang
Performance Study of Routing Algorithms for LEO Satellite Constellations
A comparative study of routing techniques is carried out on complicated LEO constellations interconnecting high speed terrestrial networks. Shortest path routing as well as optimal routing (flow deviation) methods are applied for balanced and unbalanced traffic load and for uniform and non uniform distribution of the earth stations. The performance of flow deviation method is proved to be very successful
Ioannis Gragopoulos; Evangelos Papapetrou; Fotini-Niovi Pavlidou
Finding a simple path with multiple must-include nodes
This paper presents an algorithm to find a simple path in the given network with multiple must-include nodes in the path. The problem of finding a path with must-include node(s) can be easily found in some special cases. However, in general, including multiple nodes in the simple path has been shown to be NP-Complete. This problem may arise in network
Hars Vardhan; Shreejith Billenahalli; Wanjun Huang; Miguel Razo; Arularasi Sivasankaran; Limin Tang; Paolo Monti; Marco Tacca; Andrea Fumagalli
An optimal algorithm for scheduling soft-aperiodic tasks in fixed-priority preemptive systems
A novel algorithm for servicing soft deadline aperiodic tasks in a real-time system in which hard deadline periodic tasks are scheduled using a fixed priority algorithm is presented. This algorithm is proved to be optimal in the sense that it provides the shortest aperiodic response time among all possible aperiodic service methods. Simulation studies show that it offers substantial performance
John P. Lehoczkyt; S. Ramos-thuel
Predicting functional associations from metabolism using bi-partite network algorithms
Background Metabolic reconstructions contain detailed information about metabolic enzymes and their reactants and products. These networks can be used to infer functional associations between metabolic enzymes. Many methods are based on the number of metabolites shared by two enzymes, or the shortest path between two enzymes. Metabolite sharing can miss associations between non-consecutive enzymes in a serial pathway, and shortest-path algorithms are sensitive to high-degree metabolites such as water and ATP that create connections between enzymes with little functional similarity. Results We present new, fast methods to infer functional associations in metabolic networks. A local method, the degree-corrected Poisson score, is based only on the metabolites shared by two enzymes, but uses the known metabolite degree distribution. A global method, based on graph diffusion kernels, predicts associations between enzymes that do not share metabolites. Both methods are robust to high-degree metabolites. They out-perform previous methods in predicting shared Gene Ontology (GO) annotations and in predicting experimentally observed synthetic lethal genetic interactions. Including cellular compartment information improves GO annotation predictions but degrades synthetic lethal interaction prediction. These new methods perform nearly as well as computationally demanding methods based on flux balance analysis. Conclusions We present fast, accurate methods to predict functional associations from metabolic networks. Biological significance is demonstrated by identifying enzymes whose strong metabolic correlations are missed by conventional annotations in GO, most often enzymes involved in transport vs. synthesis of the same metabolite or other enzyme pairs that share a metabolite but are separated by conventional pathway boundaries. More generally, the methods described here may be valuable for analyzing other types of networks with long-tailed degree distributions and high-degree hubs.
Learning to improve path planning performance
In robotics, path planning refers to finding a short. collision-free path from an initial robot configuration to a desired configuratioin. It has to be fast to support real-time task-level robot programming. Unfortunately, current planning techniques are still too slow to be effective, as they often require several minutes, if not hours of computation. To remedy this situation, we present and analyze a learning algorithm that uses past experience to increase future performance. The algorithm relies on an existing path planner to provide solutions to difficult tasks. From these solutions, an evolving sparse network of useful robot configurations is learned to support faster planning. More generally, the algorithm provides a speedup-learning framework in which a slow but capable planner may be improved both cost-wise and capability-wise by a faster but less capable planner coupled with experience. The basic algorithm is suitable for stationary environments, and can be extended to accommodate changing environments with on-demand experience repair and object-attached experience abstraction. To analyze the algorithm, we characterize the situations in which the adaptive planner is useful, provide quantitative bounds to predict its behavior, and confirm our theoretical results with experiments in path planning of manipulators. Our algorithm and analysis are sufficiently, general that they may also be applied to other planning domains in which experience is useful.
The prediction of radio-path characteristics
The paper examines algorithms for the long-term prediction of radio-path characteristics in the ionosphere, the main characteristic being the MUF at a given distance. The proposed approach is based on long-term memories called DATA BANKS. Attention is given to the characteritics of the various banks, including the BANK OF CITIES, the BANK OF RADIO PATHS, the REFERENCE DATA BANK, and the OUTPUT DATA BANK.
Gitina, G. M.; Kalinin, Iu. K.
Unbiased sampling of lattice Hamilton path ensembles
Hamilton paths, or Hamiltonian paths, are walks on a lattice which visit each site exactly once. They have been proposed as models of globular proteins and of compact polymers. A previously published algorithm [Mansfield, Macromolecules 27, 5924 (1994)] for sampling Hamilton paths on simple square and simple cubic lattices is tested for bias and for efficiency. Because the algorithm is a Metropolis Monte Carlo technique obviously satisfying detailed balance, we need only demonstrate ergodicity to ensure unbiased sampling. Two different tests for ergodicity (exact enumeration on small lattices, nonexhaustive enumeration on larger lattices) demonstrate ergodicity unequivocally for small lattices and provide strong support for ergodicity on larger lattices. Two other sampling algorithms [Ramakrishnan et al., J. Chem. Phys. 103, 7592 (1995); Lua et al., Polymer 45, 717 (2004)] are both known to produce biases on both 2×2×2 and 3×3×3 lattices, but it is shown here that the current algorithm gives unbiased sampling on these same lattices. Successive Hamilton paths are strongly correlated, so that many iterations are required between statistically independent samples. Rules for estimating the number of iterations needed to dissipate these correlations are given. However, the iteration time is so fast that the efficiency is still very good except on extremely large lattices. For example, even on lattices of total size 10×10×10 we are able to generate tens of thousands of uncorrelated Hamilton paths per hour of CPU time.
Mansfield, Marc L.
Path planning using optically computed potential fields
An algorithm for the optical computation of potential field maps suitable for mobile robot navigation is described and experimentally produced maps and paths are presented. The parallel analog optical computation employs a two-dimensional spatial light modulator on which an image of the potential field map is generated. Optically calculated fields contain no local minima, tend to produce paths centered in gaps between obstacles, and produce paths which give preference to wide gaps. Calculation of 128 x 128 pixel fields at a few hertz are possible with current technology, and calculation time vs. map size scales favorably in comparison to digital electronic computation.
Reid, Max B.
The shortest-graph method for calculation of the pair-correlation function in crystalline systems
A new method for approximate calculation of the pair correlation function g(r) is proposed for crystalline systems of identical particles with isotropic interactions. The main idea of the method is to account for the relative delocalization of each node in g(r) by using only the shortest lattice graph between the given points, thus neglecting smaller contributions from other (non-shortest) graphs. By employing the Lennard-Jones and Yukawa crystalline systems as representative examples, it is shown that the proposed approach yields very good agreement with the results of molecular dynamics simulations up to the melting line. The approach can be useful in approximating the structure of simple crystals (in particular, of crystalline colloids and plasma crystals), and can also be generalized for systems with anisotropic interactions.
Yurchenko, Stanislav O.
Practical path planning among movable obstacles
Path planning among movable obstacles is a practical problem that is in need of a solution. In this paper an efficient heuristic algorithm that uses a generate-and-test paradigm: a good'' candidate path is hypothesized by a global planner and subsequently verified by a local planner. In the process of formalizing the problem, we also present a technique for modeling object interactions through contact. Our algorithm has been tested on a variety of examples, and was able to generate solutions within 10 seconds. 5 figs., 27 refs.
Chen, Pang C.; Hwang, Yong K.
Definition of average path and relativity parameter computation in CASA
System CASA (computer-assisted semen analysis) is a medical applicable system which gets the sperm motility and its parameters using image processing method. But there is no any authoritative administration or academic organization gives a set of criterion for CASA now result in lowering the effective compare of work between the labs or researchers. The average path and parameters relative to it as average path velocity, amplitude of lateral head displacement and beat cross frequency are often unable to compare between systems because of different algorithm. The paper presents a new algorithm that could define the average path uniquely and compute those 3 parameters above quickly and handy from any real path.
Wu, Dawei; Huang, Yan; Chen, Xiaohua; Yu, Chang
A source-initiated on-demand routing algorithm based on the Thorup-Zwick theory for mobile wireless sensor networks.
The unreliability and dynamics of mobile wireless sensor networks make it hard to perform end-to-end communications. This paper presents a novel source-initiated on-demand routing mechanism for efficient data transmission in mobile wireless sensor networks. It explores the Thorup-Zwick theory to achieve source-initiated on-demand routing with time efficiency. It is able to find out shortest routing path between source and target in a network and transfer data in linear time. The algorithm is easy to be implemented and performed in resource-constrained mobile wireless sensor networks. We also evaluate the approach by analyzing its cost in detail. It can be seen that the approach is efficient to support data transmission in mobile wireless sensor networks. PMID:24453826
Mao, Yuxin; Zhu, Ping
Adaptive path planning for flexible manufacturing
Path planning needs to be fast to facilitate real-time robot programming. Unfortunately, current planning techniques are still too slow to be effective, as they often require several minutes, if not hours of computation. To overcome this difficulty, we present an adaptive algorithm that uses past experience to speed up future performance. It is a learning algorithm suitable for automating flexible manufacturing in incrementally-changing environments. The algorithm allows the robot to adapt to its environment by having two experience manipulation schemes: For minor environmental change, we use an object-attached experience abstraction scheme to increase the flexibility of the learned experience; for major environmental change, we use an on-demand experience repair scheme to retain those experiences that remain valid and useful. Using this algorithm, we can effectively reduce the overall robot planning time by re-using the computation result for one task to plan a path for another.
DISCUSS: Critical Path Analysis
This module, by Barrie Baker and Neville Hunt of Coventry University, introduces critical path analysis and addresses the following topics: Networks, Critical paths, Floats, Activity-on-node (AON) networks. Excel spreadsheets are used to provide examples and exercises.
Baker, Barrie; Hunt, Neville
Long Path Problems
We demonstrate the interesting, counter-intuitive result that simple paths to the global optimum can be so long that climbing the path is intractable. This means that a unimodal search space, which consists of a single hill and in which each point in the space is on a simple path to the global optimum, can be difficult for a hillclimber to
Jeffrey Horn; David E. Goldberg; Kalyanmoy Deb
Thinnest Path Problem.
We consider the thinnest path problem for secure communication in wireless ad hoc networks. For a given source and a destination, the thinnest path problem asks for a path from the source to the destination that results in the minimum number of nodes hear...
A. Swami J. Gao Q. Zhao
Reconfigurable data path processor
A reconfigurable data path processor comprises a plurality of independent processing elements. Each of the processing elements advantageously comprising an identical architecture. Each processing element comprises a plurality of data processing means for generating a potential output. Each processor is also capable of through-putting an input as a potential output with little or no processing. Each processing element comprises a conditional multiplexer having a first conditional multiplexer input, a second conditional multiplexer input and a conditional multiplexer output. A first potential output value is transmitted to the first conditional multiplexer input, and a second potential output value is transmitted to the second conditional multiplexer output. The conditional multiplexer couples either the first conditional multiplexer input or the second conditional multiplexer input to the conditional multiplexer output, according to an output control command. The output control command is generated by processing a set of arithmetic status-bits through a logical mask. The conditional multiplexer output is coupled to a first processing element output. A first set of arithmetic bits are generated according to the processing of the first processable value. A second set of arithmetic bits may be generated from a second processing operation. The selection of the arithmetic status-bits is performed by an arithmetic-status bit multiplexer selects the desired set of arithmetic status bits from among the first and second set of arithmetic status bits. The conditional multiplexer evaluates the select arithmetic status bits according to logical mask defining an algorithm for evaluating the arithmetic status bits.
Donohoe, Gregory (Inventor)
Path integral Monte Carlo simulations: Study of the efficiency of energy estimators
This article presents a study of the relative efficiency of two commonly used energy estimators for path integral Monte Carlo (MC) simulations; the Barker estimator and the virial estimator. Two different path integral MC algorithms are considered; the simple algorithm augmented with whole chain moves and the normal-mode algorithm. The behavior of the two estimators is analyzed in some model
Pedro Alexandrino Fernandes; Alfredo Palace Carvalho; J. P. Prates Ramalho
Path Planning Through Variational Dynamic Programming
The path planning problem, i.e., the geometrical problem of finding a collision-free pathbetween two given configurations of a robot moving among obstacles, has been studied bymany authors in recent years. Several complete algorithms exist for robots with few degreesof freedom (DOF), but they are intractable for more than 4 DOF. In order to tackle problems inhigher dimensions, several heuristic approaches
Jérôme Barraquand; Pierre Ferbach
Logic systems for path delay test generation
The authors present an algorithmic derivation of logic systems for solving path delay test problems. In these logic systems, the state of a signal represents any possible situation that can occur during two consecutive vectors. Starting from a set of valid input states, a state transition graph is constructed to enumerate all possible states produced by Boolean gates. Specifics of
Soumitra Bose; Prathima Agrawal; Vishwani D. Agrawal
Efficient Data Mining for Path Traversal Patterns
In this paper, we explore a new data mining capability that involves mining path traversal patterns in a distributed information-providing environment where documents or objects are linked together to facilitate interactive access. Our solution procedure consists of two steps. First, we derive an algorithm to convert the original sequence of log data into a set of maximal forward references. By
Ming-syan Chen; Jong Soo Park; Philip S. Yu
A global path planning approach for redundant manipulators
A new approach for global path planning of redundant manipulators is proposed. It poses the path planning problem as a finite time nonlinear control problem. The solution is found by a Newton-Raphson type algorithm. This technique is capable of handling various goal task descriptions as well as incorporating both joint and task space constraints. The algorithm has shown promising preliminary results in planning joint path sequences for 3R and 4R planar robots to meet Cartesian tip tracking and goal endpoint planning. It is robust with respect to local path planning problems such as singularity considerations and local minimum problems. Repetitive joint path solutions for cyclic end-effector tasks are also generated. Eventual goals of this work include implementation on full spatial robots, as well as provision of an interface for supervisory input to aid in path planning for more complex problems.
Seereeram, Sanjeev; Wen, J.
Path Relaxation: Path Planning for a Mobile Robot
Path Relaxation is a method of planning safe paths around obstacles for mobile robots. It works in two steps: a global grid starch that finds a rough path, followed by a local relaxation step that adjusts each node on the path to lower the overall path cost. The representation used by Path Relaxation allows an explicit tradeoff among length of
Charles E. Thorpe; L. Matthies
Piecewise Bezier Curves Path Planning with Continuous Curvature Constraint for Autonomous Driving
\\u000a We present two practical path planning algorithms based on Bezier curves for autonomous vehicles operating under waypoints\\u000a and corridor constraints. Bezier curves have useful properties for the trajectory generation problem. This paper describes\\u000a how the algorithms apply these properties to generate the reference trajectory for vehicles to satisfy the path constraints.\\u000a Both algorithms generate the piecewise-Bezier-curves path such that the
Ji-Wung Choi; Renwick Curry; Gabriel Elkaim
Heuristic optimization of the scanning path of particle therapy beams.
Quasidiscrete scanning is a delivery strategy for proton and ion beam therapy in which the beam is turned off when a slice is finished and a new energy must be set but not during the scanning between consecutive spots. Different scanning paths lead to different dose distributions due to the contribution of the unintended transit dose between spots. In this work an algorithm to optimize the scanning path for quasidiscrete scanned beams is presented. The classical simulated annealing algorithm is used. It is a heuristic algorithm frequently used in combinatorial optimization problems, which allows us to obtain nearly optimal solutions in acceptable running times. A study focused on the best choice of operational parameters on which the algorithm performance depends is presented. The convergence properties of the algorithm have been further improved by using the next-neighbor algorithm to generate the starting paths. Scanning paths for two clinical treatments have been optimized. The optimized paths are found to be shorter than the back-and-forth, top-to-bottom (zigzag) paths generally provided by the treatment planning systems. The gamma method has been applied to quantify the improvement achieved on the dose distribution. Results show a reduction of the transit dose when the optimized paths are used. The benefit is clear especially when the fluence per spot is low, as in the case of repainting. The minimization of the transit dose can potentially allow the use of higher beam intensities, thus decreasing the treatment time. The algorithm implemented for this work can optimize efficiently the scanning path of quasidiscrete scanned particle beams. Optimized scanning paths decrease the transit dose and lead to better dose distributions. PMID:19610293
Pardo, J; Donetti, M; Bourhaleb, F; Ansarinejad, A; Attili, A; Cirio, R; Garella, M A; Giordanengo, S; Givehchi, N; La Rosa, A; Marchetto, F; Monaco, V; Pecka, A; Peroni, C; Russo, G; Sacchi, R
Analysis of a Path Following Method for Nonsmooth Convex Programs
Recently Gilbert, Gonzaga and Karas (7) constructed examples of ill-behaved central paths for convex programs. In this paper we show that under mild conditions the central path has sucient smoothness to allow construction of a path-following interior point algorithm for non-dierentiable convex programs. We show that starting from a point near the cen- ter of the first set an †-optimal
Sanjay Mehrotra
Exploring the Interaction of Geometry and Search in Path Planning.
This thesis addressed the problem of developing path planning algorithms that are both efficient and well-behaved. The authors proposed a novel approach in which the authors solve a path planning problem by finding and solving an appropriate abstraction o...
D. J. Zhu
Comparison of Two Path Planners for Planetary Rovers.
The paper presents two path planners suitable for planetary rovers. The first is based on fuzzy description of the terrain, and genetic algorithm to find a traversable path in a rugged terrain. The second planner uses a global optimization method with a c...
M. Tarokh Z. Shiller S. Hayati
Pricing Exotic Options in a Path Integral Approach
In the framework of Black-Scholes-Merton model of financial derivatives, a path integral approach to option pricing is presented. A general formula to price European path dependent options on multidimensional assets is obtained and implemented by means of various flexible and efficient algorithms. As an example, we detail the cases of Asian, barrier knock out, reverse cliquet and basket call options,
G. Bormetti; G. Montagna; N. Moreni; O. Nicrosini
Conflict-free AGV Routing in a Bidirectional Path Layout
AGV systems are now becoming widely used in automatic material handling systems. One of the issues arisin g in applications is routing. This paper presents a bi-directional path layout an d an algorithm for routing AGVs without conflicts. Mathematical relationships among certain key parameters of path and vehicle are derived to minim ize the space requirements of the layout. The
QIU Ling; HSU Wen-Jing
Algorithmic Randomness, Physical Entropy, Measurements, and the Second Law.
Algorithmic information content is equal to the size -- in the number of bits -- of the shortest program for a universal Turing machine which can reproduce a state of a physical system. In contrast to the statistical Boltzmann-Gibbs-Shannon entropy, which...
W. H. Zurek
An iterative algorithm for delay-constrained minimum-cost multicasting
The bounded shortest multicast algorithm (BSMA) is presented for constructing minimum-cost multicast trees with delay constraints. BSMA can handle asymmetric link character- istics and variable delay bounds on destinations, specified as real values, and minimizes the total cost of a multicast routing tree. Instead of the single-pass tree construction approach used in most previous heuristics, the new algorithm is based
Mehrdad Parsa; Qing Zhu; J. J. Garcia-Luna-Aceves
Fuzzy Distance Transform: Theory, Algorithms, and Applications
This paper describes the theory and algorithms of distance transform for fuzzy subsets, called fuzzy distance transform (FDT). The notion of fuzzy distance is formulated by first defining the length of a path on a fuzzy subset and then finding the infimum of the lengths of all paths between two points. The length of a path ? in a fuzzy
Punam K. Saha; Felix W. Wehrli; Byron R. Gomberg
Locating algorithm being needless to harbor based on the quality in wireless sensor networks
From locating techniques in the wireless sensors networks two groups based on harbor and without it can be referred to. Firstly, the harbor nodes distribute the local information in the network and through that the average distance between two groups or the average length of a step is identified. Non-harbor nodes know the shortest path as the number of steps to each of the harbors and determine their distance to the harbors by understanding this average step length and using this estimation compute their location distance. Firstly, the network nodes are clustered. Each harbor is a cluster head and the cluster members using information derived from this cluster head begin locating. This process starts by the nodes located in the common field between two clusters. Although algorithm comparability based on harbor is increased by the nodes clustering, but the algorithm precise and efficiency is still dependent on the number of harbor nodes. Using harbor in all of the conditions causes its usage limitation in the wireless sensor networks. Regarding the algorithms without needing to harbor, algorithm is the first case. This algorithm has invented a new method to make a local graph in the network which is applicable in computing the relative features of nodes. Firstly, each node makes a graph with its own axis. Then the general graph of network is made and each node changes its coordinates by using an algorithm. Because of the current limitations in the trigonometry method used in this algorithm, the computed coordinates are not reliable and face difficulties in many cases. The other algorithms being needless to harbor try to use another methods instead of trigonometry methods in locating. For instance, among these methods, those ones based on graph drawing or mass and coil algorithms can be referred to. These kinds of algorithms take much time and use a lot of energy. In order to upgrade the algorithm results quality and prevent the fault distribution, we define a secondary parameter called the computed location accuracy. This parameter indicates location accuracy and can be a value between zero and one.
Sharifi, Mirali; Tousi, Fatemeh; Kazimov, Tofiq
A Fast Algorithm for Reliability Evaluation
An algorithm is developed to obtain a simplified reliability expression for a general network. All the success paths of the network are determined; then they are modified to be mutually disjoint. The reliability expression follows directly from the disjoint paths. The algorithm is easy and computationally economical. The reliability expression involves fewer terms and arithmetic operations than any of the
K. K. Aggarwal; K. B. Misra; J. S. Gupta
Path Following Robot.
Given a desired path to be followed by a Robot, a set of commands must be given to the Robot joint servos so that the Robot Tip, or Endpoint, can follow that path. These commands must be synchronized in time and scaled so as to maintain accuracy in the pr...
S. G. Goodway
Advanced Physics: Path Integral
A cursor is shown in an x-y graph. The cursor can be dragged around the graph and its path is marked as it is moved. The data are sent to a DataTable which shows x, y, and the value of the path integral, F.dl.
Christian, Wolfgang; Belloni, Mario
Operational transfer path analysis
One of the tools used to study the NVH behaviour of a system is the transfer path analysis. It aims to identify the operational forces and the propagation paths of the vibrations and is especially interesting in the case when the system is composed of different subsystems. The classical techniques identify the transfer paths when the system is disassembled. This way one eliminates flanking transfer paths. Yet it is very time-consuming and the boundary conditions are not correct anymore. The presented method makes it possible to identify the transfer paths without disassembling the system. The advantages are that the overall testing time is reduced and that the real boundary conditions are present. In this article the theory will be reviewed and it will be validated using data generated by finite element simulations.
De Sitter, Gert; Devriendt, Christof; Guillaume, Patrick; Pruyt, Erik
Fracturing the optimal paths.
Optimal paths play a fundamental role in numerous physical applications ranging from random polymers to brittle fracture, from the flow through porous media to information propagation. Here for the first time we explore the path that is activated once this optimal path fails and what happens when this new path also fails and so on, until the system is completely disconnected. In fact many applications can also be found for this novel fracture problem. In the limit of strong disorder, our results show that all the cracks are located on a single self-similar connected line of fractal dimension D(b) approximately = 1.22. For weak disorder, the number of cracks spreads all over the entire network before global connectivity is lost. Strikingly, the disconnecting path (backbone) is, however, completely independent on the disorder. PMID:20366106
Andrade, J S; Oliveira, E A; Moreira, A A; Herrmann, H J
Path Relaxation: Path Planning for a Mobile Robot.
Path Relaxation is a method of planning safe paths around obstacles for mobile robots. It works in two steps: a global grid search that finds a rough path, followed by a local relaxation step that adjusts each node on the path to lower the overall path co...
C. E. Thorpe
An attempt of microwave CT system which discriminates the transmission path by means of time domain measurement.
A microwave-based computed tomography system was developed based on a method that uses time domain measurement to determine the shortest path of propagation components between two antennas. The method calculates shortest path of propagation components by examining mixer output DC components, delivering similar precision as chirp-pulse microwave computed tomography. Because post-mixer signal processing need only concerns DC currents, the effects of overshoot characteristics of baseband filters and the like are removed, simplifying measurement. System circuit composition is also simplified, lowering system costs. This paper provides a theoretical framework for the method, an S-parameter verification of the theory, and an experimental verification using a basic hardware construction. Results showed a restored image from the measurement data, indicating the utility of the method for microwave imaging. PMID:22255201
Tamura, Mutsumi; Ogawa, Takahiro; Miyakawa, Michio
Scheduling of Tasks in Multiprocessor System Using Hybrid Genetic Algorithms
This paper presents an investigation into the optimal scheduling of real-time tasks of a multiprocessor system using hybrid\\u000a genetic algorithms (GAs). A comparative study of heuristic approaches such as 'Earliest Deadline First (EDF)' and 'Shortest\\u000a Computation Time First (SCTF)' and genetic algorithm is explored and demonstrated. The results of the simulation study using\\u000a MATLAB is presented and discussed. Finally, conclusions
Betzy Varghes; Alamgir Hossain; Keshav Dahal
Call-graph-based inter-class MM path generation
Inter-class testing is the testing of classes for composing an object-oriented system or subsystem during integration. MM Path is defined as an interleaved sequence of method executions linked by messages. It represents the interactions between methods in object-oriented software well, hence fits for object-oriented integration testing. However, the current MM Path generation methods only support intra-class testing. In this paper, a call-graph-based approach is proposed to promote MM Path automatic generation from intra-class to inter-class level. The approach is evaluated by controlled experiments on 12 Java benchmark programs with two typical call graph construction algorithms, Class Hierarchy Analysis and Anderson's Points-to Analysis. Then, the impact of the two algorithms on inter-class MM path generation efficiency is studied. The result shows that our approach is practicable and Anderson's Points-to Analysis outperforms Class Hierarchy Analysis for inter-class MM Path generation.
He, Wei; Zhao, Ruilian
Dynamic path planning in sensor-based terrain acquisition
The terrain acquisition problem is formulated as that of continuous motion planning, and no constraints are imposed on obstacle geometry. Two algorithms are described for acquiring planar terrains with obstacles of arbitrary shape. Estimates of the algorithm performance are derived as upper bounds on the lengths of generated paths
V. J. Lumelsky; S. Mukhopadhyay; K. Sun
Robust detection of audio watermarks after acoustic path transmission
This paper presents an algorithm to improve the robustness of audio watermarks after acoustic path transmission. This includes a brief presentation of the variety of signal alterations a watermarked audio track undergo in such a scenario. After presenting the underlying audio watermarking algorithm, the involved effects with respect to the correlation based detection will be discussed. Based on this observations
Michael Arnold; Peter G. Baum; Xiao-Ming Chen
Natural decomposition of free space for path planning
This paper describes an algorithm that decomposes the free space into nonoverlapping geometric-shaped primitives suitable for path planning. Given a set of polygonal obstacles in space, the algorithm first decomposes concave obstacles into connecting convex obstacles in order to have a uniform obstacle representation, which facilitates later processing. The neighborhood relations among these Convex obstacles are identified and then used
Darwin T. Kuan; James C. Zamiska; Rodney A. Brooks
Triaging the right patient to the right place in the shortest time.
Trauma systems have been successful in saving lives and preventing disability. Making sure that the right patient gets the right treatment in the shortest possible time is integral to this success. Most trauma systems have not fully developed trauma triage to optimize outcomes. For trauma triage to be effective, there must be a well-developed pre-hospital system with an efficient dispatch system and adequately resourced ambulance system. Hospitals must have clear designations of the level of service provided and agreed protocols for reception of patients. The response within the hospital must be targeted to ensure the sickest patients get an immediate response. To enable the most appropriate response to trauma patients across the system, a well-developed monitoring programme must be in place to ensure constant refinement of the clinical response. This article gives a brief overview of the current approach to triaging trauma from time of dispatch to definitive treatment. PMID:24961786
Cameron, P A; Gabbe, B J; Smith, K; Mitra, B
Automatic path searching for minimally invasive neurosurgical planning
We are developing a neurosurgical planning system, and this paper presents a method of automatic path searching from skin surface of the head to tumor inside the brain. The path obtained by our system is an optimal one in minimally invasive neurosurgery and it is calculated automatically based on a 3D atlas. The 3D atlas is a voxel based 3D matrix, and consists of two parts, structural part and knowledge part. The structural part includes the geometrical information with respect to each tissue. The knowledge part is generated based on experiences of doctors, and numeric value is provided as importance value for each tissue. The path searching consists of two steps, path finding and path smoothing. Path finding is to select an optimal path from surface of the head to the affected part based on minimization of importance value integrating along with the path. We applied the algorithm into a head MRI data set. The path obtained by path finding is reformed smoothly to approach the natural path of surgeon.
Fujii, Tetsuya; Asakura, Hiroki; Emoto, Hiroshi; Sugou, Nobuo; Mito, Toshiaki; Shibata, Iekado
NEGOTIATING THE CRITICAL PATH..................................................................................................7 SCIENTIFIC AND TECHNICAL DIMENSIONS ALONG THE CRITICAL PATH...................................9 A BETTER PRODUCT DEVELOPMENT TOOLKIT IS URGENTLY NEEDED ..................................11 TOOLS FOR ASSESSING SAFETY......................................................................................................16 Towards a Better Safety Toolkit................................................................................................17 Getting to the Right Safety Standards......................................................................................20 TOOLS FOR DEMONSTRATING MEDICAL UTILITY .......................................................................20 Towards a Better Effectiveness Toolkit ...................................................................................21 Getting to the Right Effectiveness Standards .........................................................................25 TOOLS FOR CHARACTERIZATION AND MANUFACTURING .........................................................25 Towards a Better Manufacturing Toolkit.................................................................................27 Getting to the Right Manufacturing Standards .......................................................................28 A PATH FORWARD .............................................................................................................................29 The Orphan Products Grant Program.
Method to update the coefficients of the secondary path filter under active noise control
In active noise control systems using a filtered-x algorithm, the secondary path must be identified before the coefficients of the noise control filter are updated. The secondary path, however, has an impulse response that is continually changing in practical systems. This change degrades noise reduction and the stability of the system. Therefore, the coefficients of the secondary path filter must
Kensaku Fujii; Juro Ohga
Collision-free Path Planning and Trajectory Generation for MAVs Flying in Urban Terrain
This paper presents an optimal algorithm for finding collision-free path and trajectory for microair vehicles (MAVs) in urban terrain where multiple ground obstacles are distributed. Regarding vertices of polygonal obstacles as input points of the Delaunay triangulations, a Delaunay-based path planning is proposed to determine an optimal waypoint path while considering criterions of minimum fuel expenditure and collision risk. A
Rong Zhu; Xiaoying Guan; Zhaoying Zhou; Dong Sun
Processor Controlpath Microarchitecture Synthesis Based on the A* Algorithm.
The paper describes the integration of methods from artificial intelligence in the synthesis of microarchitectures for processor control paths. For control path and finite state machine synthesis many algorithms are known. Unfortunately all these algorith...
A. J. W. M. ten Berg
Tool paths and cutting technology in computer-aided process planning
This paper reports on the development of a module to calculate automatically tool paths and cutting conditions for metal cutting operations. Process planning must select correct cutting conditions to minimise disturbances on the shop floor owing to tooling problems. Tool path and cutting condition algorithms to generate reliable NC programs have been designed. The algorithms have been implemented in the
R. M. Boogert; H. J. J. Kals; F. J. A. M. van Houten
Critical Path Method Reports.
The computer system for the Critical Path Method Reports consists of three programs. The programs are CPM Calculation, CPM Calendar Dating and CPM Time-Sequence Plot. The CPM Calculations Program is used for doing the arithmetic calculations associated wi...
R. C. Tennent
Air Vehicle Path Planning.
This dissertation explores optimal path planning for air vehicles. An air vehicle exposed to illumination by a tracking radar is considered and the problem of determining an optimal planar trajectory connecting two prespecified points is addressed. An ana...
J. M. Hebert
Tortuous path chemical preconcentrator
A non-planar, tortuous path chemical preconcentrator has a high internal surface area having a heatable sorptive coating that can be used to selectively collect and concentrate one or more chemical species of interest from a fluid stream that can be rapidly released as a concentrated plug into an analytical or microanalytical chain for separation and detection. The non-planar chemical preconcentrator comprises a sorptive support structure having a tortuous flow path. The tortuosity provides repeated twists, turns, and bends to the flow, thereby increasing the interfacial contact between sample fluid stream and the sorptive material. The tortuous path also provides more opportunities for desorption and readsorption of volatile species. Further, the thermal efficiency of the tortuous path chemical preconcentrator is comparable or superior to the prior non-planar chemical preconcentrator. Finally, the tortuosity can be varied in different directions to optimize flow rates during the adsorption and desorption phases of operation of the preconcentrator.
Manginell, Ronald P. (Albuquerque, NM); Lewis, Patrick R. (Albuquerque, NM); Adkins, Douglas R. (Albuquerque, NM); Wheeler, David R. (Albuquerque, NM); Simonson, Robert J. (Cedar Crest, NM)
A Path to Discovery
The path taken and the turns made as a turtle traces a polygon are examined to discover an important theorem in geometry. A unique tool, the Angle Adder, is implemented in the investigation. (Contains 9 figures.)
Stegemoller, William; Stegemoller, Rebecca
Path integral learning of multidimensional movement trajectories
This paper explores the use of Path Integral Methods, particularly several variants of the recent Path Integral Policy Improvement (PI2) algorithm in multidimensional movement parametrized policy learning. We rely on Dynamic Movement Primitives (DMPs) to codify discrete and rhythmic trajectories, and apply the PI2-CMA and PIBB methods in the learning of optimal policy parameters, according to different cost functions that inherently encode movement objectives. Additionally we merge both of these variants and propose the PIBB-CMA algorithm, comparing all of them with the vanilla version of PI2. From the obtained results we conclude that PIBB-CMA surpasses all other methods in terms of convergence speed and iterative final cost, which leads to an increased interest in its application to more complex robotic problems.
André, Joa~o.; Santos, Cristina; Costa, Lino
Follow the Paths
In this lesson, younger students will be introduced to the various orbital paths that are used for satellites. Using a globe and a satellite model or a large picture of Earth, the teacher will introduce three types of orbital paths (polar, elliptical, and geosynchronous). The students should be able to define 'satellite', define the three types of orbits, describe how satellites orbit the Earth, and understand how they are slowed down by drag from the atmosphere.
Singularity Free Path Planning for Parallel Robots
In this paper, we present a procedure to automatically generate the kinematic model of parallel mechanisms as well as an algorithm\\u000a for their singularity free path planning. Singular positions are considered as obstacles that have to be bypassed while moving\\u000a toward the goal. The 3-RPR planar parallel robot was taken as an example to illustrate the effectiveness of the procedure.
Samir Lahouar; Saďd Zeghloul; Lotfl Romdhane
Deep Space Formation Flying Spacecraft Path Planning
Efficient algorithms for collision-free energy sub-optimal path plan- ning for formations of spacecraft flying in deep space are presented. The idea is to introduce a set of way-points through which the space- craft are required to pass, combined with parameterizations of the trajectories which are energy-optimal for each spacecraft. The re- sulting constrained optimization problem is formulated as a quasi-
Cornel Sultan; Sanjeev Seereeram; Raman K. Mehra
Distributed routing using internodal coordination
A distributed algorithm for the dynamic calculation of the shortest paths in a computer network is introduced. The algorithm is loop-free at every instant of time independently of the transmission and processing delays in the network or the changes in the topology. According to the algorithm, each node maintains the length of the shortest paths to each network destination; update
J. J. Garcia-Luna-Aceves
Non-isoparametric tool path planning by machining strip evaluation for 5-axis sculptured surface machining
Presented in this paper is a new approach to 5-axis NC tool path generation for sculptured surface machining. Techniques of feasible machining strip evaluation are used for non-isoparametric 5-axis tool path generation. A searching algorithm is proposed to find the parameter increments of adjacent cutter locations along orthogonal path intervals for optimal non-isoparametric path generation. Compared to the use of
Yuan-shin Lee
Spatial fingerprint of quantum path interferences in high order harmonic generation.
We have spatially and spectrally resolved the high order harmonic emission from an argon gas target. Under proper phase matching conditions we were able to observe for the first time the spatial fine structure originating from the interference of the two shortest quantum paths in the harmonic beam. The structure can be explained by the intensity-dependent harmonic phase of the contributions from the two paths. The spatially and spectrally resolved measurements are consistent with previous spatially integrated results. Our measurement method represents a new tool to clearly distinguish between different interference effects and to potentially observe higher order trajectories in the future with improved detection sensitivity. Here, we demonstrate additional experimental evidence that the observed interference pattern is only due to quantum-path interferences and cannot be explained by a phase modulation effect. Our experimental results are fully supported by simulations using the strong field approximation and including propagation. PMID:20174127
Schapper, F; Holler, M; Auguste, T; Zaďr, A; Weger, M; Saličres, P; Gallmann, L; Keller, U
Image-based path planning for automated virtual colonoscopy navigation
Virtual colonoscopy (VC) is a noninvasive method for colonic polyp screening, by reconstructing three-dimensional models of the colon using computerized tomography (CT). In virtual colonoscopy fly-through navigation, it is crucial to generate an optimal camera path for efficient clinical examination. In conventional methods, the centerline of the colon lumen is usually used as the camera path. In order to extract colon centerline, some time consuming pre-processing algorithms must be performed before the fly-through navigation, such as colon segmentation, distance transformation, or topological thinning. In this paper, we present an efficient image-based path planning algorithm for automated virtual colonoscopy fly-through navigation without the requirement of any pre-processing. Our algorithm only needs the physician to provide a seed point as the starting camera position using 2D axial CT images. A wide angle fisheye camera model is used to generate a depth image from the current camera position. Two types of navigational landmarks, safe regions and target regions are extracted from the depth images. Camera position and its corresponding view direction are then determined using these landmarks. The experimental results show that the generated paths are accurate and increase the user comfort during the fly-through navigation. Moreover, because of the efficiency of our path planning algorithm and rendering algorithm, our VC fly-through navigation system can still guarantee 30 FPS.
Hong, Wei
Performance Study of Adaptive Routing Algorithms for LEO Satellite Constellations under Self-Similar and Poisson Traffic