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

K. Gao, P. N. Suganthan, T. Chua
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引用次数: 3

Abstract

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.
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基于pareto的离散和谐搜索算法求解柔性作业车间调度
提出了一种基于pareto的离散和谐搜索(PDHS)算法求解多目标FJSP问题。目标是最小化两个标准,即最大的完成时间(Makespan)和平均早、晚。首先,提出了一种初始化机器分配任务的新方法。本文还采用了一些现有的启发式方法来初始化和声记忆。因此,在和谐内存中,用离散的机器排列填充机器分配,用作业排列填充操作顺序。其次,我们开发了一种新的即兴规则,以产生一种新的FJSP和声。分别对机器分配和操作顺序进行了处理。第三,嵌入了多种局部搜索方法,增强了算法的局部开发能力;最后,利用已知的基准实例进行了大量的计算实验。计算结果和比较表明,本文提出的基于pareto的离散和谐搜索算法求解多目标柔性作业车间调度问题是有效的。
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