Optimization of Project Scheduling Activities in Dynamic CPM and PERT
  Networks Using Genetic Algorithms
  Projects consist of interconnected dimensions such as objective, time,
resource and environment. Use of these dimensions in a controlled way and their
effective scheduling brings the project success. Project scheduling process
includes defining project activities, and estimation of time and resources to
be used for the activities. At this point, the project resource-scheduling
problems have begun to attract more attention after Program Evaluation and
Review Technique (PERT) and Critical Path Method (CPM) are developed one after
the other. However, complexity and difficulty of CPM and PERT processes led to
the use of these techniques through artificial intelligence methods such as
Genetic Algorithm (GA). In this study, an algorithm was proposed and developed,
which determines critical path, critical activities and project completion
duration by using GA, instead of CPM and PERT techniques used for network
analysis within the scope of project management. The purpose of using GA was
that these algorithms are an effective method for solution of complex
optimization problems. Therefore, correct decisions can be made for implemented
project activities by using obtained results. Thus, optimum results were
obtained in a shorter time than the CPM and PERT techniques by using the model
based on the dynamic algorithm. It is expected that this study will contribute
to the performance field (time, speed, low error etc.) of other studies.
