An effective coding approach for multiobjective integrated resource selection and operation sequences problem |
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Authors: | Haipeng Zhang Mitsuo Gen Yoonho Seo |
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Affiliation: | (1) Graduate School of Information, Production & Systems, Waseda University, 808-0135 Kitakyushu, Japan;(2) Department of Industrial Systems and Information Engineering, Korea University, 136-713 Seoul, Korea |
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Abstract: | In this paper, we consider an integrated Resource Selection and Operation Sequences (iRS/OS) problem in Intelligent Manufacturing System (IMS). Several kinds of objectives are taken into account, in which the makespan for orders should be minimized; workloads among machine tools should be balanced; the total transition times between machines in a local plant should also be minimized. To solve this multiobjective iRS/OS model, a new two vectors-based coding approach has been proposed to improve the efficiency by designing a chromosome containing two kinds of information, i.e., operation sequences and machine selection. Using such kind of chromosome, we adapt multistage operation-based Genetic Algorithm (moGA) to find the Pareto optimal solutions. Moreover a special technique called left-shift hillclimber has been used as one kind of local search to improve the efficiency of our algorithm. Finally, the experimental results of several iRS/OS problems indicate that our proposed approach can obtain best solutions. Further more comparing with previous approaches, moGA performs better for finding Pareto solutions. Received: May 2005/Accepted: December 2005 |
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Keywords: | Intelligent manufacturing system Integrated resource selection and operation sequences Multistage operation-based genetic algorithm Left-shift hillclimber Multiple criteria model |
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