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首页> 外文期刊>International journal of production economics >A hybrid algorithm for the multi-stage flow shop group scheduling with sequence-dependent setup and transportation times
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A hybrid algorithm for the multi-stage flow shop group scheduling with sequence-dependent setup and transportation times

机译：基于序列的建立和运输时间的多阶段流水车间群调度的混合算法

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This study investigates the multi-stage flow shop group scheduling problem with job transportation times between machines and sequence-dependent setup times between groups. The objective is to minimize the makespan (F-m vertical bar fmls, S-plk, t(ijk), prmu vertical bar C-max). It is known that this problem is NP-hard and generalizes the typical multi-stage group scheduling problems. In this paper, a coding scheme is proposed to simultaneously determine both the sequence of jobs in each group and the sequence of groups. By reasonably combining particle swarm optimization (PSO) and genetic algorithms (GA), a fast and easily implemented hybrid algorithm (HA) is developed for solving the considered problem. The effectiveness and efficiency of the proposed HA are demonstrated and compared with those of standard PSO and GA by numerical results of various test instances with group numbers up to 20. In addition, three different lower bounds are developed to evaluate the solution quality of HA. Numerical results indicate that the proposed HA is a viable and effective approach for the studied multi-stage flow shop group scheduling problem. (C) 2015 Elsevier B.V. All rights reserved.
机译：这项研究调查了多阶段的流水车间组调度问题，其中包括机器之间的作业运输时间和组之间依赖序列的建立时间。目的是最小化制造跨度（F-m垂直线fmls，S-plk，t（ijk），prmu垂直线C-max）。已知该问题是NP难的，并且概括了典型的多阶段组调度问题。在本文中，提出了一种编码方案，可以同时确定每个组中的作业顺序和组中的顺序。通过合理组合粒子群优化（PSO）和遗传算法（GA），开发了一种快速且易于实现的混合算法（HA）以解决所考虑的问题。通过组数最多为20的各种测试实例的数值结果，证明了所提出的HA的有效性和效率，并将其与标准PSO和GA的有效性和效率进行了比较。此外，还开发了三个不同的下限来评估HA的解决方案质量。数值结果表明，所提出的HA是解决多阶段流水车间群调度问题的可行且有效的方法。 （C）2015 Elsevier B.V.保留所有权利。

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