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A multiobjective evolutionary algorithm for the process planning of flexible manufacturing systems  

김여근 (전남대학교 산업공학과)
신경석 (전남대학교 고품질전기전자부품 및 시스템 연구센터)
김재윤 (전남대학교 고품질전기전자부품 및 시스템 연구센터)
Publication Information
Journal of the Korean Operations Research and Management Science Society / v.29, no.2, 2004 , pp. 77-95 More about this Journal
Abstract
This paper deals with the process planning of flexible manufacturing systems (FMS) with various flexibilities and multiple objectives. The consideration of the manufacturing flexibility is crucial for the efficient utilization of FMS. The machine, tool, sequence, and process flexibilities are considered In this research. The flexibilities cause to increase the Problem complexity. To solve the process planning problem, an this paper an evolutionary algorithm is used as a methodology. The algorithm is named multiobjective competitive evolutionary algorithm (MOCEA), which is developed in this research. The feature of MOCEA is the incorporation of competitive coevolution in the existing multiobjective evolutionary algorithm. In MOCEA competitive coevolution plays a role to encourage population diversity. This results in the improvement of solution quality and, that is, leads to find diverse and good solutions. Good solutions means near or true Pareto optimal solutions. To verify the Performance of MOCEA, the extensive experiments are performed with various test-bed problems that have distinct levels of variations in the four kinds of flexibilities. The experiments reveal that MOCEA is a promising approach to the multiobjective process planning of FMS.
Keywords
FMS; Process Planning; Multiobjective Evolutionary Algorithm; Competitive Coevolution;
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