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A genetic algorithm application for multi-objective multi-project resource constrained project scheduling problem

Küçüksayacigil, Fikri and Ulusoy, Gündüz (2014) A genetic algorithm application for multi-objective multi-project resource constrained project scheduling problem. In: 15th Workshop of the EURO Working Group, Istanbul, Turkey

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Abstract

Resource Constrained Project Scheduling Problem (RCPSP) has been studied extensively by researchers by considering limited renewable and non-renewable resources. Several exact and heuristic methods have been proposed. Some important extensions of RCPSP such as multi-mode RCPSP, multi-objective RCPSP and multi-project RCPSP have also been focused. In this study, we consider multi-project and multi-objective resource constrained project scheduling problem. As a solution method, non-dominated sorting genetic algorithm (NSGA-II) is adopted. By experimenting with different crossover and parent selection mechanisms, a detailed fine-tuning process is conducted, in which response surface optimization method is employed. In order to improve the solution quality, backward-forward pass (BFP) procedure is proposed as both post-processing as well as for new population generation. The performance of the algorithm and CPU times are reported. The results show that backward-forward pass procedure is successful to improve the solution quality.

Item Type:Papers in Conference Proceedings
Uncontrolled Keywords:RCPSP, Genetic Algorithms,Multi-objective RCPSP, Multi-project RCPSP, backward-forward scheduling
Subjects:T Technology > T Technology (General) > T055.4-60.8 Industrial engineering. Management engineering
ID Code:24084
Deposited By:Gündüz Ulusoy
Deposited On:18 Jun 2014 11:49
Last Modified:02 Nov 2015 15:00

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