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The capacitated lot-sizing and scheduling problem with sequence-dependent setup costs and setup times

机译:容量受限的批量确定和计划问题,其取决于序列的设置成本和设置时间

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We consider the single machine capacitated lot-sizing and scheduling problem (CLSP) with sequence-dependent setup costs and non-zero setup times, with the additional feature that setups may be carried over from one period to the next, and that setups are preserved over idle periods. We provide an exact formulation of this problem as a mixed-integer program. It is well known that the CLSP is NP-hard. Therefore, we have also developed a heuristic for solving large problem instances. This is coupled with a procedure for obtaining a lower bound on the optimal solution. We carry out a computational study to test the accuracy of several different lower bounding linear relaxations and the approximate solution obtained by the heuristic. In our study, the average deviation of the heuristic solution from the corresponding exact solution depends on the size of the problem and ranges from 10 to 16%. The heuristic is more effective when there are many more products than there are planning periods. This is a desirable property from a practical viewpoint since most firms are likely to implement such a procedure on a rolling horizon basis, solving the problem repeatedly for a few periods at a time.
机译:我们考虑了单机容量批量和调度问题(CLSP),它具有与序列相关的设置成本和非零设置时间,其附加功能是可以将设置从一个期间转移到下一个期间,并保留设置在闲置期间。我们提供此问题的精确表述作为混合整数程序。众所周知,CLSP是NP硬的。因此,我们还开发了一种解决大型问题实例的启发式方法。这与获得最佳解决方案下限的过程结合在一起。我们进行了计算研究,以测试几种不同的下界线性松弛的准确性以及通过启发式方法获得的近似解。在我们的研究中,启发式解决方案与相应精确解决方案的平均偏差取决于问题的大小,范围为10%至16%。当产品数量超过计划周期时,启发式方法会更有效。从实践的角度来看,这是一个理想的属性,因为大多数公司可能会在滚动的基础上实施这样的程序,一次几次重复地解决问题。

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