Optimal Production Scheduling using a Production Simulator and Multi-population Global-best Modified Brain Storm Optimization

This paper proposes an optimal production scheduling method using the production simulator and multi-population global-best modified brain storm optimization (MP-GMBSO). Currently, in industry sector, decarbonization and carbon neutrality are approached by technical innovations such as Industry 4.0. In particular, optimal production scheduling researches which are important in production environments have been conducted actively. However, there is a gap between the previous optimal production scheduling researches and production schedule generating methods of practical production environments. The proposed method can fill the gap and it can be applied to the practical production environments. Results of the proposed method are compared with those of the conventional MBSO [7] and GMBSO based methods. It is verified that the proposed MP-GMBSO based method can find higher quality production schedules. In addition, it is verified that there is a significant difference among the conventional MBSO and GMBSO based methods, and the proposed MP-GMBSO based method with 0.05 significant level by the Friedman test as a priori test and the Wilcoxon signed rank test with Bonferroni-Holm correction as a post hoc test. In addition, the objective function of the target production scheduling has needles and it is found that the problem is one of the challenging problems to be optimized. The proposed MP-GMBSO based method can solve the problem better than the conventional MBSO and GMBSO based methods even with the challenging characteristic of the problem.