An effective coding approach for multiobjective integrated resource selection and operation sequences problem
- Authors
- Zhang, Haipeng; Gen, Mitsuo; Seo, Yoonho
- Issue Date
- 8월-2006
- Publisher
- SPRINGER
- Keywords
- intelligent manufacturing system; integrated resource selection and operation sequences; multistage operation-based genetic algorithm; left-shift hillclimber; multiple criteria model
- Citation
- JOURNAL OF INTELLIGENT MANUFACTURING, v.17, no.4, pp.385 - 397
- Indexed
- SCIE
SCOPUS
- Journal Title
- JOURNAL OF INTELLIGENT MANUFACTURING
- Volume
- 17
- Number
- 4
- Start Page
- 385
- End Page
- 397
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/123121
- DOI
- 10.1007/s10845-005-0012-y
- ISSN
- 0956-5515
- 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.
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Collections - College of Engineering > School of Industrial and Management Engineering > 1. Journal Articles
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