Hybrid genetic algorithm with adaptive abilities for resource-constrained multiple project scheduling

Authors:
KwanWoo Kim;YoungSu Yun;JungMo Yoon;Mitsuo Gen;Genji Yamazaki
Affiliations:
Department of Intelligent Systems, Tokyo Metropolitan Institute of Technology, Tokyo 190-0065, Japan;School of Automotive, Industrial & Mechanical Engineering, Daegu University, Kyungbook 712-714, Korea;Department of Computer Science Engineering, Seoul National University of Technology, Seoul 139-743, Korea;Graduate School of Information, Production & Systems, Waseda University, Kitakyushu 808-0135, Japan;Department of Intelligent Systems, Tokyo Metropolitan Institute of Technology, Tokyo 190-0065, Japan
Venue:
Computers in Industry - Special issue: Application of genetics algorithms in industry
Year:
2005

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Abstract

In this paper, we propose a hybrid genetic algorithm with fuzzy logic controller (flc-hGA) to solve the resource-constrained multiple project scheduling problem (rc-mPSP) which is well known NP-hard problem. Objectives described in this paper are to minimize total project time and to minimize total tardiness penalty. However, it is difficult to treat the rc-mPSP problems with traditional optimization techniques. The proposed new approach is based on the design of genetic operators with fuzzy logic controller (FLC) through initializing the revised serial method which outperforms the non-preemptive scheduling with precedence and resources constraints. For these rc-mPSP problems, we demonstrate that the proposed flc-hGA yields better results than conventional genetic algorithms and adaptive genetic algorithm.