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Variable neighbourhood search for minimising tardiness objectives on flow shop with batch processing machines

机译:可变邻域搜索,用于使用批处理机器将流水车间中的拖延目标最小化

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This paper presents the scheduling problem on flow shop with many batch processing machines (BPM) to minimise total tardiness, maximum tardiness and number of tardy jobs, respectively. We propose an efficient variable neighbourhood search (VNS) for the problem, in which job permutation is the only optimisation object and the solutions of batch formation and batch scheduling can be directly obtained by using the permutation. To obtain the promising results, an initial solution of VNS is first produced and then one insertion operation and two swap operations are applied to improve the solution. The proposed VNS is finally tested and the computational results show its good performance on many-BPM flow shop scheduling.
机译:本文提出了具有许多批处理机器(BPM)的流水车间上的调度问题,以分别使总拖延,最大拖延和迟到的作业数量最小化。我们针对该问题提出了一种有效的变量邻域搜索(VNS),其中工作置换是唯一的优化对象,并且可以使用置换直接获得批处理形成和批处理计划的解决方案。为了获得有希望的结果,首先生成VNS的初始解决方案,然后应用一个插入操作和两个交换操作来改进该解决方案。最后对提出的VNS进行了测试,计算结果表明了其在多BPM流水车间调度中的良好性能。

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