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A General Heuristic for Production Planning Problems

机译:生产计划问题的一般启发式

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We consider production planning problems with the restriction that all integer variables model Setups. Since finding a feasible solution of such problems is in general NP-complete, the classical approaches have been the use of heuristics to find good feasible Solutions on the one hand, or branch and cut on the other hand. In the case of the former, a dual bound is not available, and there is no guarantee of solution quality. For the latter, the accent has been on improving the dual bound and only the simplest schemes have been used to find good feasible Solutions. Here we first show that such simple schemes may run into trouble, even when applied to very simple problems. This motivates the proposed heuristic, IPE, which is designed to be used within a branch-and-cut approach. We test the Performance of the heuristic on various published lot-sizing and network-design problems, with and without tightened reformulations. We compare these results with other heuristics and with time truncated branch-and-bound searches. IPE appears to be the best choice for large problems with weak formulations.
机译:我们考虑了所有整数变量都可以对安装程序建模的限制的生产计划问题。由于找到此类问题的可行解决方案通常是NP完全的,因此经典方法一直是使用启发式方法一方面找到良好的可行解决方案,或者另一方面进行分支和割除。在前者的情况下,不存在双重限制,并且不能保证解决方案的质量。对于后者,重点放在改善对偶边界上,并且仅使用最简单的方案来找到好的可行解决方案。在这里,我们首先表明,即使将这些简单的方案应用于非常简单的问题,也可能会遇到麻烦。这激发了提议的启发式IPE,该启发式IPE旨在用于分支剪切方法中。在有或没有严格的重新制定公式的情况下,我们针对各种已发布的批量确定和网络设计问题测试了启发式算法的性能。我们将这些结果与其他启发式方法和时间截断的分支定界搜索进行比较。对于配方较弱的大问题,IPE似乎是最佳选择。

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