SOLVING RESOURCE-CONSTRAINED PROJECT SCHEDULING PROBLEM USING GENETIC ALGORITHM | ||||
| Journal of Al-Azhar University Engineering Sector | ||||
| Article 27, Volume 12, Issue 42, January 2017, Page 187-198 PDF (650.6 K) | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/auej.2017.19298 | ||||
 View on SCiNiTO | ||||
| Authors | ||||
| Raafat Elshaer; Mona shawky; Hesham Elawady; Gamal Nawara | ||||
| Industrial Engineering Department, Faculty of Engineering, Zagazig University, Sharkia, Egypt | ||||
| Abstract | ||||
| Due to the combinatorial nature of the resource-constrained project scheduling problem (RCPSP), there is a lot of artificial intelligence methods proposed to solve it. The Genetic Algorithm (GA), one of these methods, is considered to be a valuable search algorithm capable of finding a reasonable solution in a short computational time. The primary objective of this paper is to build a genetic algorithm for solving RCPSP problem aiming at minimizing project’s makespan. Based on a comprehensive review of different GAs and a full factorial experiment, a proposed GA has been presented. The proposed algorithm has been tested on a well-known benchmark (PSPLIB). The computation results show that the proposed GA outperforms many published algorithms and on average performs as well as other algorithms. Also, the performance of the algorithm improves in solving large scale problems | ||||
| Keywords | ||||
| Resource Constrained Project Scheduling problems; Genetic Algorithm; Project makespan | ||||
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