A Hybrid Multiobjective Evolutionary Approach for Flexible Job-Shop Scheduling Problems

Jian Xiong, Xu Tan, Ke-wei Yang, Li-ning Xing and Ying-wu Chen

Mathematical Problems in Engineering, 2012, vol. 2012, 1-27

Abstract:

This paper addresses multiobjective flexible job-shop scheduling problem (FJSP) with three simultaneously considered objectives: minimizing makespan, minimizing total workload, and minimizing maximal workload. A hybrid multiobjective evolutionary approach (H-MOEA) is developed to solve the problem. According to the characteristic of FJSP, a modified crowding distance measure is introduced to maintain the diversity of individuals. In the proposed H-MOEA, well-designed chromosome representation and genetic operators are developed for FJSP. Moreover, a local search procedure based on critical path theory is incorporated in H-MOEA to improve the convergence ability of the algorithm. Experiment results on several well-known benchmark instances demonstrate the efficiency and stability of the proposed algorithm. The comparison with other recently published approaches validates that H-MOEA can obtain Pareto-optimal solutions with better quality and/or diversity.

Date: 2012
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:478981

DOI: 10.1155/2012/478981

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