Title: Artificial bee colony algorithm for fuzzy job shop scheduling

Authors: You-Lian Zheng; Yuan-Xiang Li

Addresses: Faculty of Mathematics and Computer Science, Hubei University, Wuhan 430062, China; State Key Laboratory of Software Engineering, Wuhan University, Wuhan 430072, China. ' State Key Laboratory of Software Engineering, Wuhan University, Wuhan 430072, China

Abstract: Artificial bee colony (ABC) is one of the most recently introduced swarm-based algorithms inspired by the intelligent foraging behaviour of honeybee swarm. In this study, ABC is applied to solve fuzzy job shop scheduling problems to investigate the advantage of ABC on fuzzy scheduling. In ABC, an operation-based coding and decoding procedure is adopted and neighbourhood structure based on insertion operator is proposed. In each cycle, the employed bee phase and the onlooker bee phase execute sequentially, no scouts are considered and the worst food source is replaced with the elite solution every certain cycles. ABC is applied to some instances and compared with the methods from the literature. Computational results show the promising advantage of ABC on fuzzy scheduling.

Keywords: artificial bee colony; fuzzy scheduling; job shop scheduling; neighbourhood structure; swarm intelligence; intelligent foraging.

DOI: 10.1504/IJCAT.2012.048682

International Journal of Computer Applications in Technology, 2012 Vol.44 No.2, pp.124 - 129

Available online: 20 Aug 2012 *

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