A simple and effective evolutionary algorithm for multiobjective flexible job shop scheduling

Tsung-Che Chiang and Hsiao-Jou Lin

International Journal of Production Economics, 2013, vol. 141, issue 1, 87-98

Abstract: This paper addresses the multiobjective flexible job shop scheduling problem (MOFJSP) regarding minimizing the makespan, total workload, and maximum workload. The problem is solved in a Pareto manner, whose goal is to seek for the set of Pareto optimal solutions. We propose a multiobjective evolutionary algorithm, which utilizes effective genetic operators and maintains population diversity carefully. A main feature of the proposed algorithm is its simplicity—it needs only two parameters. Performance of our algorithm is compared with seven state-of-the-art algorithms on fifteen popular benchmark instances. Only our algorithm can find 70% or more non-dominated solutions for every instance.

Keywords: Flexible job shop scheduling; Multiobjective optimization; Pareto optimal; Evolutionary algorithm (search for similar items in EconPapers)
Date: 2013
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Citations: View citations in EconPapers (11)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:proeco:v:141:y:2013:i:1:p:87-98

DOI: 10.1016/j.ijpe.2012.03.034

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