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Pareto-based discrete harmony search algorithm for flexible job shop scheduling

机译:基于帕累托的离散和声搜索算法,实现柔性作业车间调度

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This paper proposes a pareto-based discrete harmony search (PDHS) algorithm to solve multi-objective FJSP. The objectives are the minimization of two criteria namely, the maximum of the completion time (Makespan) and the mean earliness and tardiness. Firstly, we develop a new method for the initial the machine assignment task. Some existing heuristics are also employed for initializing the harmony memory. Hence, harmony memory is filled with discrete machine permutation for machine assignment and job permutation for operation sequence. Secondly, we develop a new rule for the improvisation to produce a new harmony for FJSP. The machine assignment and operation sequence are processed respectively. Thirdly, several local search methods are embedded to enhance the algorithm's local exploitation ability. Finally, extensive computational experiments are carried out using well-known benchmark instances. Computational results and comparisons show the efficiency and effectiveness of the proposed pareto-based discrete harmony search algorithm for solving the multi-objective flexible job-shop scheduling problem.
机译:提出了一种基于Pareto的离散和谐搜索(PDHS)算法来解决多目标FJSP问题。目标是最小化两个标准,即完成时间的最大值(Makespan)和平均早期及迟到。首先,我们为初始机器分配任务开发了一种新方法。一些现有的启发式方法也用于初始化和声记忆。因此,和谐存储器充满了用于机器分配的离散机器排列和用于操作序列的作业排列。其次,我们为即兴创作制定了新规则,以使FJSP产生新的和谐。机器分配和操作顺序分别进行处理。第三,嵌入了几种局部搜索方法,以提高算法的局部开发能力。最后,使用众所周知的基准实例进行了广泛的计算实验。计算结果和比较结果表明,所提出的基于pareto的离散和谐搜索算法可以解决多目标柔性Job-shop调度问题。

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