Flexible Job-Shop Rescheduling for New Job Insertion by Using Discrete Jaya Algorithm
Flexible Job-Shop Rescheduling for New Job Insertion by Using Discrete Jaya Algorithm
复制标题
使用离散 Jaya 算法灵活地重新安排作业车间以插入新作业
DOI：
10.1109/tcyb.2018.2817240
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发表时间：
2019
影响因子：
11.8
通讯作者：
Suganthan Ponnuthurai Nagaratnam
中科院分区：
文献类型：
--
作者：
Gao Kaizhou;Yang Fajun;Zhou MengChu;Pan Quanke;Suganthan Ponnuthurai Nagaratnam
当必须将新到达的优先作业插入现有计划时，重新计划是灵活作业车间的必要程序。不稳定性衡量对现有日程安排的更改量，是评估重新安排解决方案质量的重要指标。本文重点研究用于新作业插入的灵活作业车间重新调度问题（FJRP）。首先，制定了FJRP，用于泵再制造带来的新工作插入。本文涉及双目标 FJRP，以最大限度地减少：1) 不稳定性和 2) 以下指标之一：a) 完工时间； b) 总流动时间； c) 机器工作负载； d) 机器总工作负载。接下来，它离散化一种新颖且简单的元启发式算法，名为 Jaya，得到 DJaya 并对其进行改进以解决 FJRP。采用两种简单的启发式方法来初始化高质量的解决方案。最后，提出了五个面向目标的本地搜索算子和四个组合来提高 DJaya 的性能。最后，它对七个不同规模的泵再制造实际案例进行了实验，并将 DJaya 与一些最先进的算法进行了比较。结果表明，DJaya 对于解决相关 FJRP 问题是有效且高效的。
Rescheduling is a necessary procedure for a flexible job shop when newly arrived priority jobs must be inserted into an existing schedule. Instability measures the amount of change made to the existing schedule and is an important metrics to evaluate the quality of rescheduling solutions. This paper focuses on a flexible job-shop rescheduling problem (FJRP) for new job insertion. First, it formulates FJRP for new job insertion arising from pump remanufacturing. This paper deals with bi-objective FJRPs to minimize: 1) instability and 2) one of the following indices: a) makespan; b) total flow time; c) machine workload; and d) total machine workload. Next, it discretizes a novel and simple metaheuristic, named Jaya, resulting in DJaya and improves it to solve FJRP. Two simple heuristics are employed to initialize high-quality solutions. Finally, it proposes five objective-oriented local search operators and four ensembles of them to improve the performance of DJaya. Finally, it performs experiments on seven real-life cases with different scales from pump remanufacturing and compares DJaya with some state-of-the-art algorithms. The results show that DJaya is effective and efficient for solving the concerned FJRPs.