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A kernel search to the multi-plant capacitated lot sizing problem with setup carry-over

机译:通过设置结转对多工厂容量批量问题进行内核搜索

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Lot sizing is one of the most challenging problems in production planning. This paper focuses on the multi-plant capacitated lot sizing problem (MPCLSP) with setup carry-over (MPCLSP-SC). To the best of our knowledge, the MPCLSP-SC has been the subject of one single study, despite the fact that it can bring financial benefits, primarily by considering case studies under tight capacity. Moreover, in spite of the significant improvement in the performance of benchmark optimization solvers over the years, they are still very time and memory consuming for large MPCLSP instances. Therefore, heuristics stand out among the solution methods to tackle this type of problem. This paper introduces a novel matheuristic, a kernel search (KS) method, to solve the MPCLSP-SC. Through computational experiments, it was possible to show the outstanding performance of the proposed method for large instances with diverse characteristics. The experiments also demonstrate that the introduced KS outperformed state-of-the-art methods to solve the MPCLSP. (C) 2018 Elsevier Ltd. All rights reserved.
机译:批量确定是生产计划中最具挑战性的问题之一。本文着重讨论带有设置结转(MPCLSP-SC)的多工厂容量批量问题(MPCLSP)。据我们所知,尽管MPCLSP-SC可以带来财务收益,但它主要是通过考虑能力有限的案例研究而进行的一项研究。而且,尽管多年来基准测试优化求解器的性能有了显着提高,但对于大型MPCLSP实例,它们仍然非常耗时且消耗内存。因此,启发式方法在解决此类问题的解决方法中脱颖而出。本文介绍了一种新颖的数学方法,即核搜索(KS)方法,以解决MPCLSP-SC问题。通过计算实验,可以证明该方法在具有各种特征的大型实例中的出色性能。实验还证明,引入的KS优于解决MPCLSP的最新方法。 (C)2018 Elsevier Ltd.保留所有权利。

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