A hybrid genetic algorithm for multi mode resource constrained scheduling problem for large size projects

Thesis Type: Postgraduate

Institution Of The Thesis: Orta Doğu Teknik Üniversitesi, Faculty of Engineering, Department of Civil Engineering, Turkey

Approval Date: 2015


Supervisor: RİFAT SÖNMEZ


Just like in all industries, some of the available resources, in order to finish a project on time, are constrained in construction industry. To be able to finish the project on time has high importance both for the contractor and for the owner. Project scheduling in which resources are limited for a particular time are called as resource constrained project scheduling problems (RCPSP) and occupies a significant place in construction management. Especially for large scale projects, little success has been achieved for solving multi-mode RCPSP. In the context of this thesis, RCPSPs with multiple execution modes for activities, are aimed to be solved. With Hybrid Genetic Algorithm (HGA) proposed in this thesis, finding the optimal solutions for large size construction projects with multiple execution modes and resource constraints is aimed. The proposed hybrid algorithm consists of two parts, first part is a heuristic method and second part is a hybrid genetic algorithm. In the first part, some of the population is generated with a heuristic method so that search domain of the algorithm can be concentrated on better results. In second part, Hybrid Genetic Algorithm, solutions are improved with each generation. The performance of the algorithm is verified with the examples available in the literature. The main contribution of this algorithm is that it enables the large sized real life projects to be solved with resource constraints in a fast and efficient way.