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Minimizing total time deviation from due windows for jobs with multiple delivery due windows using lot-streaming in permutation flow shops

机译:使用置换流水车间中的批量流,将具有多个交货到期窗口的作业的到期窗口与总时间偏差最小化

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摘要

This paper studies splitting of jobs items into sublots to be processed in a permutation flow shop with sublot-attached setups using lot streaming. The objective is to minimize the total time deviation from due windows subject to the assumption of several due windows per job. We present a decomposition based solution heuristic to assign sublots into dispatching positions, followed by a mixed-integer linear programming model to obtain sublot numbers, sublot sizes and the schedule. The solution obtained is improved using a genetic algorithm. Numerical results are provided to prove the effectiveness of the approach.
机译:本文研究了将作业项拆分为子批处理,然后在带有子批处理附加设置的置换流水车间中使用批量流处理的方法。目的是在假设每个作业有几个到期窗口的前提下,使与到期窗口的总时间偏差最小化。我们提出了一种基于分解的启发式解决方案,将子批分配到调度位置,然后采用混合整数线性规划模型来获得子批号,子批大小和调度。使用遗传算法改进了获得的解决方案。数值结果证明了该方法的有效性。

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