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A jigsaw puzzle inspired algorithm for solving large-scale no-wait flow shop scheduling problems
Applied Intelligence ( IF 3.4 ) Pub Date : 2019-07-02 , DOI: 10.1007/s10489-019-01497-2
Fuqing Zhao , Xuan He , Yi Zhang , Wenchang Lei , Weimin Ma , Chuck Zhang , Houbin Song

Abstract

The no-wait flow shop scheduling problem (NWFSP), as a typical NP-hard problem, has important ramifications in the modern industry. In this paper, a jigsaw puzzle inspired heuristic (JPA) is proposed for solving NWFSP with the objective of minimizing makespan. The core idea behind JPA is to find the best match for each job until all the jobs are scheduled in the set of process. In JPA, a waiting time matrix is constructed to measure the gap between two jobs. Then, a matching matrix based on the waiting time matrix is obtained. Finally, the optimal scheduling sequence is built by using the matching matrix. Experimental results on large-scale benchmark instances show that JPA is superior to the state-of-the-art heuristics.



中文翻译:

一种拼图游戏启发式算法,用于解决大规模的无等待流水车间调度问题

摘要

作为典型的NP难题,无等待流水车间调度问题(NWFSP)在现代工业中具有重要的意义。本文提出了一种拼图拼图启发式启发法(JPA),用于解决NWFSP,其目的是最大程度地缩短制造时间。JPA的核心思想是为每个作业找到最佳匹配,直到在该流程集中安排了所有作业为止。在JPA中,构造了一个等待时间矩阵来衡量两个作业之间的差距。然后,获得基于等待时间矩阵的匹配矩阵。最后,利用匹配矩阵建立最优调度序列。在大型基准实例上的实验结果表明,JPA优于最新的启发式方法。

更新日期:2020-01-04
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