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Projects consist of interconnected dimensions such as objective, time,resource and environment. Use of these dimensions in a controlled way and theireffective scheduling brings the project success. Project scheduling processincludes defining project activities, and estimation of time and resources tobe used for the activities. At this point, the project resource-schedulingproblems have begun to attract more attention after Program Evaluation andReview Technique (PERT) and Critical Path Method (CPM) are developed one afterthe other. However, complexity and difficulty of CPM and PERT processes led tothe use of these techniques through artificial intelligence methods such asGenetic Algorithm (GA). In this study, an algorithm was proposed and developed,which determines critical path, critical activities and project completionduration by using GA, instead of CPM and PERT techniques used for networkanalysis within the scope of project management. The purpose of using GA wasthat these algorithms are an effective method for solution of complexoptimization problems. Therefore, correct decisions can be made for implementedproject activities by using obtained results. Thus, optimum results wereobtained in a shorter time than the CPM and PERT techniques by using the modelbased on the dynamic algorithm. It is expected that this study will contributeto the performance field (time, speed, low error etc.) of other studies.

Optimization of Project Scheduling Activities in Dynamic CPM and PERT Networks Using Genetic Algorithms