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Sequence-dependent flow shop scheduling problem minimising the number of tardy jobs

机译:与序列有关的流水车间调度问题,可将迟到的作业数量降至最低

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Flow shop scheduling problems with sequence-dependent setup times and minimising the number of tardy jobs as the criterion (F_m|prmu, S_(ijk|∑U_j) are considered in this research. A mixed-integer linear programming model is developed for the research problem. Since the proposed research problem has been proven to be NP-hard, several meta-heuristic algorithms based on tabu search (TS) and the imperialist competitive algorithm (ICA) are proposed to heuristically solve the problem. In order to find the best meta-heuristic algorithm, random test problems, ranging in size from small, medium, to large, are generated and solved by the meta-heuristic algorithms. Then, a detailed statistical experiment based on the split-plot design is performed to find the best meta-heuristic algorithm. The results of the experiment show that the performance of ICA is worse than the other algorithms for small- and medium-sized problems. The hybrid of ICA and the TS algorithm provides better performance than the other proposed algorithms for large-sized problems.
机译:考虑序列依赖的建立时间并以延迟工作的数量最小为标准的F_m | prmu,S_(ijk | ∑U_j)的流水车间调度问题,建立了混合整数线性规划模型由于已证明所提出的研究问题是NP难的,因此提出了几种基于禁忌搜索(TS)和帝国主义竞争算法(ICA)的元启发式算法,以启发式方式解决该问题,从而找到最佳解决方案。元启发式算法通过元启发式算法生成并解决了大小不等的随机测试问题,然后,基于分裂图设计进行了详细的统计实验,以找到最佳方法。元启发式算法,实验结果表明,对于中小型问题,ICA的性能比其他算法差; ICA和TS算法的混合提供了比传统算法更好的性能。其他针对大型问题的建议算法。

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