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Indexed by:Journal Papers

Date of Publication:2010-01-01

Journal:International Journal of Production Research

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 optimalsolution with classical methods due to a high computational complexity(NP-hard). According to the nature of JSS, an improved definition of the JSSproblem is presented and a JSS model based on a novel algorithm is establishedthrough 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, whichincludes assembly problems, is proposed. The designed DSS decoding geneticalgorithm (GA) can avoid the appearance of infeasible solutions throughcomparing current genes with DSS in the decoding procedure to obtain workingprocedure which can be decoded. Finally, the effectiveness and superiority of theproposed method is clarified compared to the classical JSS methods throughthe simulation experiments and the benchmark problem.