A simple and effective evolutionary algorithm for multiobjective flexible job shop scheduling |
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Authors: | Tsung-Che Chiang Hsiao-Jou Lin |
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Affiliation: | Department of Computer Science and Information Engineering, National Taiwan Normal University, Taiwan, ROC |
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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. |
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