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Iterated Local Search Algorithm for Flexible Job Shop Scheduling

机译：灵活的车间调度的迭代局部搜索算法

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摘要

The flexible job shop scheduling problem (FJSSP) is an extension of the classical job shop scheduling problem (JSSP). The classical JSSP determines the job sequence for each machine. In contrast, FJSSP decides not only the job sequence but also the machine assignment for jobs; thus, it is a combinatorial optimization problem of a larger scale. To efficiently solve an FJSSP, which is non-deterministic polynomial-time hard, we require a heuristic method. In previous studies, the FJSSP has been solved by neighborhood algorithms, which employ various metaheuristic methods. Some approaches constrain the neighborhood operation from jobs on a critical path and simultaneously change the machine assignment and job sequence. However, a method that can independently change machine assignment and job sequence may improve the efficiency of FJSSP because the solution of JSSP already exists. In this study, we investigate the effect of continuing to change job sequence and machine assignment, and job sequence and machine assignment change are iterated using a local search method. In numerical experiments, the effects of the frequency of job sequence change and machine assignment change on the performance of the solution are investigated. Finally, we find the best machine assignment and job sequence change method for FJSSP.
机译：灵活的作业车间调度问题（FJSSP）是经典作业车间调度问题（JSSP）的扩展。经典的JSSP确定每台机器的作业顺序。相反，FJSSP不仅决定作业顺序，还决定作业的机器分配。因此，这是一个较大规模的组合优化问题。为了有效地解决非确定性多项式时间困难的FJSSP，我们需要一种启发式方法。在以前的研究中，FJSSP已通过采用各种元启发式方法的邻域算法解决。一些方法将邻居操作限制在关键路径上的作业上，并同时更改机器分配和作业顺序。但是，可以独立更改机器分配和作业顺序的方法可以提高FJSSP的效率，因为已经存在JSSP解决方案。在这项研究中，我们调查了继续更改作业顺序和机器分配的影响，并使用局部搜索方法迭代了作业序列和机器分配的变化。在数值实验中，研究了工作顺序更改频率和机器分配更改对解决方案性能的影响。最后，我们找到了FJSSP的最佳机器分配和作业顺序更改方法。

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