PSO with improved strategy and topology for job shop scheduling

Authors:
Kun Tu;Zhifeng Hao;Ming Chen
Affiliations:
College of Computer Science and Engineering, South China University of Technology, Guangzhou, P.R. China;College of Computer Science and Engineering, South China University of Technology, Guangzhou, P.R. China;National Mobile Communications Research Laboratory, Southeast University, Nanjing, P.R. China
Venue:
ICNC'06 Proceedings of the Second international conference on Advances in Natural Computation - Volume Part II
Year:
2006

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Abstract

Particle swarm optimization (PSO) has proven to be a promising heuristic algorithm for solving combinatorial optimization problems. However, N-P hard problems such as Job Shop Scheduling (JSSP) are difficult for most heuristic algorithms to solve. In this paper, two effective strategies are proposed to enhance the searching ability of the PSO. An alternate topology is introduced to gather better information from the neighborhood of an individual. Benchmarks of JSSP are used to test the approaches. The experiment results indicate that the improved Particle Swarm has a good performance with a faster searching speed in the search space of JSSP.