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Indexed by:Journal Papers

Date of Publication:2011-06-15

Journal:INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH

Included Journals:Scopus、SCIE、EI

Volume:49

Issue:12

Page Number:3585-3604

ISSN No.:0020-7543

Key Words:job-shop scheduling; genetic algorithm; decode select string decoding; assembling work

Abstract:With job-shop scheduling (JSS) it is usually difficult to achieve the optimal solution with classical methods due to a high computational complexity (NP-hard). According to the nature of JSS, an improved definition of the JSS problem is presented and a JSS model based on a novel algorithm is established through the analysis of working procedure, working data, precedence constraints, processing performance index, JSS algorithm and so on. A decode select string (DSS) decoding genetic algorithm based on operation coding modes, which includes assembly problems, is proposed. The designed DSS decoding genetic algorithm (GA) can avoid the appearance of infeasible solutions through comparing current genes with DSS in the decoding procedure to obtain working procedure which can be decoded. Finally, the effectiveness and superiority of the proposed method is clarified compared to the classical JSS methods through the simulation experiments and the benchmark problem.