Polytope complexes are the generalisation of polygon meshes in geo-information systems (GIS) to arbitrary dimension, and a natural concept for accessing spatio-temporal information. Complexes of each dimension have a straight-forward dimension-independent database representation called "Relational Complex". Accordingly, complex overlay is the corresponding generalisation of map overlay in GIS to arbitrary dimension. Such overlay can be computed by partitioning the cells into simplices, intersecting these and finally combine their intersections into the resulting overlay complex. Simplex partitioning, however, can expensive in dimension higher than 2. In the case of polytope complex overlay signed simplicial decomposition is an alternative. This paper presents a purely combinatoric polytope complex decomposition which ignores geometry. In particular, this method is also a decomposition method for non-convex polytopes. Geometric n-D-simplex intersection is then done by a simplified active-set-method---a well-known numerical optimisation method. "Summing" up the simplex intersections then yields the desired overlay complex.
@cite_10: We show that generating all negative cycles of a weighted graph is a hard enumeration problem, in both the directed and undirected cases. More precisely, given a family of negative (directed) cycles, it is an NP-complete problem to decide whether this family can be extended or there are no other negative (directed) cycles in the graph, implying that (directed) negative cycles cannot be generated in polynomial output time, unless P=NP. As a corollary, we solve in the negative two well-known generating problems from linear programming: (i) Given an infeasible system of linear inequalities, generating all minimal infeasible subsystems is hard. Yet, for generating maximal feasible subsystems the complexity remains open. (ii) Given a feasible system of linear inequalities, generating all vertices of the corresponding polyhedron is hard. Yet, in the case of bounded polyhedra the complexity remains open. Equiva lently, the complexity of generating vertices and extreme rays of polyhedra remains open.
Much work has been done on polytope decomposition, volume computation, and intersection---mostly, however, on convex polytopes represented by vertices (via convex hull) or by (intersecting) half spaces. That representations do not allow non-convex polytopes and some of the above mentioned problems (even vertex enumeration) are NP-hard if no fixed dimension upper bound is given @cite_10 . By using instead, vertices, edges, faces etc. are already enumerated as a precondition and the above problems can be avoided.