Dinamik CPM ve PERT Ağlarında Genetik Algoritmalar Kullanarak Proje Çizelgeleme Aktivitelerinin Optimizasyonu
Projeler; amaç, zaman, kaynak ve çevre olmak üzere birbirleriyle ilişkili birtakım boyutlardan oluşmaktadır. Bu boyutların kontrollü kullanılması ve etkin planlanması proje başarısını getirmektedir. Proje planlama süreci, proje faaliyetlerinin tanımlanması ve projedeki faaliyetler için zaman ve kaynak tahmini yapılması süreçlerini kapsar. Bu noktada, proje kaynak planlama problemleri, Program Değerlendirme ve Gözden Geçirme Tekniği (PERT) ve Kritik Yol Metodu (CPM) birbiri ardına geliştirildikten sonra daha fazla dikkat çekmiştir. Bununla birlikte, CPM ve PERT işlemlerinin karmaşıklığı ve zorluğu, bu teknikleri Genetik Algoritma (GA) gibi yapay zeka yöntemleri ile kullanmaya itmiştir. Bu çalışmada, proje yönetimi kapsamında şebeke analizi için kullanılan CPM ve PERT tekniklerinin yerine, GA kullanılarak kritik yol, kritik faaliyet ve proje tamamlanma süresini belirleyen bir algoritma önerilmiş ve geliştirilmiştir. GA kullanılmasının amacı, bu algoritmaların karmaşık optimizasyon problemlerin çözümünde etkili bir yöntem olmasıdır. Böylece, elde edilen sonuçlar kullanılarak gerçekleştirilecek proje faaliyetleriyle ilgili doğru kararlar alınabilmektedir. Nitekim, geliştirilen dinamik algoritma ile CPM ve PERT tekniklerinden daha kısa sürede optimum sonuçlara ulaşılmıştır. Çalışmanın diğer çalışmaların performans alanına (zaman, hız, düşük hata vb.) katkı sağlaması beklenmektedir.
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 theireffective scheduling brings the project success. Project scheduling process includesdefining project activities, and estimation of time and resources to be used for theactivities. At this point, the project resource-scheduling problems have begun toattract 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 thesetechniques through artificial intelligence methods such as Genetic Algorithm (GA).In this study, an algorithm was proposed and developed, which determines criticalpath, critical activities and project completion duration by using GA, instead ofCPM and PERT techniques used for network analysis within the scope of projectmanagement. The purpose of using GA was that these algorithms are an effectivemethod for solution of complex optimization problems. Therefore, correctdecisions can be made for implemented project activities by using obtained results.Thus, optimum results were obtained in a shorter time than the CPM and PERTtechniques by using the model based on the dynamic algorithm. It is expected thatthis study will contribute to the performance field (time, speed, low error etc.) ofother studies.
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