KAYNAK KISITLI PROJE ÇİZELGELEME PROBLEMİNDE TEKRARSIZ KROMOZOM DESTEKLİ PARALEL GENETİK ALGORİTMA UYGULAMASI. - EBESEK, Şafak; YAMAN, Hakan (Journal of International Social Research / Uluslararası Sosyal Araştırmalar Dergisi, 2019)
Resource constrained project scheduling is a combinatorial optimization problem. The duration of the activities, resource requests, precedence relations and the limits of the resources to be used were strictly determined. The goal is minimizing the makespan of project. Despite the simplicity of its definition, the resource constrained project scheduling problems (RCPSP) belongs to the class of NP-hard optimization problems and is actually one of the most intractable classical problems in practice. The exact methods developed to solve resource constrained project scheduling problems are time consuming and useless, especially when solving large problems. Metaheuristics are mostly useful to reach good quality solutions in reasonable computational times and are suitable for practical problems, which often have large dimensions and very complex constraints. The solution of resource constrained project scheduling problems with Metaheuristics is one of the intensive working areas. It was determined during the literature review and gap analysis what improvements and supports for Genetic Algorithm (GA) could be effective. The main idea behind the improvement and support applied in this study is to achieve nonrepetition and increase diversification. The application has been developed on MATLAB environment and has been tested on Project Scheduling Problem Library (PSPLIB) problems which are used as standard for measuring the performance values of resource constrained project scheduling problems. The average deviation values obtained as a result of the solutions of the problems: J30 and J60 problems are at the top band with other top studies having equal results, J120 problems are ranked as sixth and have minor gaps comparing with other top studies. The best new solution has been reached on problem J120_35_5. The solution has been approved and appended on the official website of the Technical University of Munich, which hosted the PSPLIB problems. Improvements and supports applied in this study can be used as a guide for new studies on resource constrained project scheduling problems.