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Artificial bee colony algorithm for scheduling and rescheduling fuzzy flexible job shop problem with new job insertion

机译:具有新工作插入的模糊柔性作业车间问题调度与重新调度的人工蜂群算法

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摘要

This study addresses flexible job shop scheduling problem (FJSP) with two constraints, namely fuzzy processing time and new job insertion. The uncertainty of processing time and new job insertion are two scheduling related characteristics in remanufacturing. Fuzzy processing time is used to describe the uncertainty in processing time. Rescheduling operator is executed when new job(s) is (are) inserted into the schedule currently being executed. A two-stage artificial bee colony (TABC) algorithm with several improvements is proposed to solve FJSP with fuzzy processing time and new job insertion constraints. Also, several new solution generation methods and improvement strategies are proposed and compared with each other. The objective is to minimize maximum fuzzy completion time. Eight instances from remanufacturing are solved using the proposed TABC algorithm. The proposed improvement strategies are compared and discussed in detail. Two proposed ABC algorithms with the best performances are compared against seven existing algorithms over by five benchmark cases. The optimization results and comparisons show the competitiveness of the proposed TABC algorithm for solving FJSP. (C) 2016 Elsevier B.V. All rights reserved.
机译:本研究针对具有两个约束条件的灵活的作业车间调度问题(FJSP),即模糊处理时间和新作业插入。处理时间的不确定性和新工作的插入是再制造中与调度相关的两个特征。模糊处理时间用于描述处理时间的不确定性。当新作业被插入当前正在执行的计划中时,将执行重新计划运算符。针对具有模糊处理时间和新的工作插入约束的FJSP,提出了一种改进的两阶段人工蜂群算法。此外,提出了几种新的解决方案生成方法和改进策略,并将它们相互比较。目的是最小化最大模糊完成时间。使用提出的TABC算法解决了再制造的八个实例。对提出的改进策略进行了比较和详细讨论。在五个基准案例的基础上,将两种提出的性能最佳的ABC算法与七种现有算法进行了比较。优化结果和比较结果表明,所提出的TABC算法在解决FJSP方面具有竞争力。 (C)2016 Elsevier B.V.保留所有权利。

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