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An artificial bee colony algorithm approach for unrelated parallel machine scheduling with processing set restrictions, job sequence-dependent setup times, and due date

机译:具有处理集限制,与作业序列有关的设置时间和到期日期的无关并行机器调度的人工蜂群算法方法

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摘要

The problem dealt with in this study has job sequence-dependent setup times under suitable machine constraints and due date constraints. The performance criterion for this problem is to minimize the sum of makespan and total tardiness. In the literature, an application of ABC algorithm for the problems which includes all the properties that we have dealt has not been discussed. Because there is no appropriate test data, a real-life data was collected from a factory. In this study, a new approach has been proposed for the solution with meta-heuristics of unrelated parallel machine scheduling problems which is a combinatorial problem. This new neighborhood approach provides different machine assignments for every candidate job sequences. This approach is used by integrating into ABC and GA. To evaluate the performances of the algorithms, the real-life problem was solved by using ABC and GA algorithms under similar conditions. It was found that all jobs can be completed in two shifts without the need for a third shift. Computational results show that ABC algorithm has better performance than GA.
机译:在这项研究中要解决的问题是在适当的机器约束和到期日约束下,取决于作业顺序的设置时间。此问题的性能标准是最小化制造期和总拖延时间。在文献中,尚未讨论将ABC算法应用于包含我们已处理的所有特性的问题。由于没有适当的测试数据,因此从工厂收集了真实数据。在这项研究中,已经提出了一种新的方法来解决不相关的并行机器调度问题的元启发式问题,这是一个组合问题。这种新的邻域方法为每个候选作业序列提供了不同的机器分配。通过集成到ABC和GA中使用此方法。为了评估算法的性能,通过在相似条件下使用ABC和GA算法解决了现实生活中的问题。已经发现,所有工作可以分两班完成,而无需第三班。计算结果表明,ABC算法具有比GA更好的性能。

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