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Two-stage, single-lot, lot streaming problem for a hybrid flow shop

机译:混合流水车间的两阶段,单批次,大量流问题

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In this paper, we address a single-lot, lot streaming problem for a two-stage hybrid flow shop, which consists of one machine at Stage 1 and two parallel (identical) machines at Stage 2. The objective is to minimize makespan. The lot is to be split into sublots each of which is processed first on the machine at Stage 1, and then, on one of the machines at Stage 2. A sublot-attached removal time is incurred after processing each sublot at Stage 1. First, we assume the number of sublots for the lot to be known a priori and develop closed-form expressions to obtain optimal, continuous sublot sizes for this case. Then, we consider determination of an optimal number of sublots in addition to their sizes. We develop an upper bound on the number of sublots, , and use an algorithm of complexity in conjunction with the closed-form expressions for sublot sizes to obtain an optimal solution. We also address the problem of determining number of sublots and integer sublot sizes, and propose a heuristic method for its solution that relies on some key results from the continuous case of the problem. The results of our numerical experimentation reveal the efficacy of the proposed method to obtain near-optimal integer sublot sizes and makespan values that are within 2.35 % of the true optimum for the testbed of data used, each obtained within a few seconds of CPU time.
机译:在本文中,我们解决了两阶段混合流水车间的单批次批量流问题,该车间由第1阶段的一台机器和第2阶段的两台并行(相同)机器组成。目标是最大程度地缩短制造时间。该批次将分成多个子批,每个子批首先在阶段1的机器上进行处理,然后在阶段2的其中一台机器上进行处理。在阶段1处理每个子批后,将产生附加子批的清除时间。 ,我们假设先验已知批次的子批次数量,并开发出封闭形式的表达式以获得这种情况下的最佳连续子批次大小。然后,我们考虑确定除其大小以外的子批的最佳数量。我们开发了子批次数量的上限,并将复杂度算法与子批次大小的封闭形式表达式结合使用以获得最佳解决方案。我们还解决了确定子批数量和整数子批大小的问题,并提出了一种启发式方法来解决该问题,该方法依赖于问题连续性情况下的一些关键结果。我们的数值实验结果表明,该方法可有效获得接近最佳的整数子批大小,并且使生成值在所用数据测试台的真实最佳值的2.35%以内,且每种值均在几秒钟的CPU时间内获得。

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