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Solution space analysis and feasible genetic algorithm for assembly job-shop scheduling problems

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Indexed by:期刊论文

Date of Publication:2009-09-21

Journal:Materials Science Forum

Included Journals:EI、CPCI-S、Scopus

Volume:626 627

Page Number:705-710

ISSN No.:0878493115

Key Words:Assembly Job-shop Scheduling Problem; Feasible solution space; Fix operator; Feasible Genetic algorithm

Abstract:The classical job-shop scheduling problems (JSP) become assembly job-shop scheduling problems (AJSP) if assembly constraints are attached to them. The entire solution space size and the feasible one of AJSP are analyzed and obtained by utilizing combinational mathematics. It is proved that the feasible solution space takes extremely small portion of the entire one. To minimize the makespan of AJSP, genetic algorithm searching in feasible solution space (FGA) is proposed and designed, and the search range of FGA is limited to feasible solution space. Finally, benchmarks tests and results are given which demonstrate the advantage and efficiency of FGA. © (2009) Trans Tech Publications, Switzerland.

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