Optimal Production Scheduling using a Production Simulator by Modified Brain Storm Optimization

This paper proposes optimal production scheduling using a practical production simulator and modified brain storm optimization (MBSO). So far, in a production scheduling research area, for the purpose of practical applications, various practical performance measures and constraints have been proposed. Recently, production scheduling researches in consideration of energy consumptions and CO
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emissions have been conducted. However, in the various production scheduling researches, each research only treats practical performance measures, practical constraints, energy consumptions, and CO
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emissions partially. Hence, no researches have considered the various practical performance measures and constraints, energy consumptions, and CO
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emissions totally. In this paper, a production schedule optimization framework is proposed using a production simulator considering constraints that cannot be mathematically formulated. It is verified that the proposed MBSO based method can find higher quality solutions than the conventional PSO and DEEPSO based methods. It is also verified that there is a significant difference among the conventional PSO and DEEPSO based methods, and the proposed MBSO based method with 0.05 significant level using the Friedman test.