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A relax-and-fix with fix-and-optimize heuristic applied to multi-level lot-sizing problems

机译:具有修复和优化启发式的放松和修复功能,适用于多级批量确定问题

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摘要

In this paper, we propose a simple but efficient heuristic that combines construction and improvement heuristic ideas to solve multi-level lot-sizing problems. A relax-and-fix heuristic is firstly used to build an initial solution, and this is further improved by applying a fix-and-optimize heuristic. We also introduce a novel way to define the mixed-integer subproblems solved by both heuristics. The efficiency of the approach is evaluated solving two different classes of multi-level lot-sizing problems: the multi-level capacitated lot-sizing problem with backlogging and the two-stage glass container production scheduling problem (TGCPSP). We present extensive computational results including four test sets of the Multi-item Lot-Sizing with Backlogging library, and real-world test problems defined for the TGCPSP, where we benchmark against state-of-the-art methods from the recent literature. The computational results show that our combined heuristic approach is very efficient and competitive, outperforming benchmark methods for most of the test problems.
机译:在本文中,我们提出了一种简单而有效的启发式方法,该方法结合了构造和改进启发式思想,以解决多层次的批量问题。首先使用放松和固定启发式算法来构建初始解决方案,然后通过应用固定并优化启发式算法进一步改进。我们还介绍了一种新颖的方法来定义由两种启发式方法解决的混合整数子问题。评估了该方法的效率,解决了两类不同的多级批量问题:带积压的多级容量批量问题和两阶段玻璃容器生产调度问题(TGCPSP)。我们提供了广泛的计算结果,包括带积压库的多项目批量测量的四个测试集,以及为TGCPSP定义的实际测试问题,我们在此参考最新文献中的最新方法。计算结果表明,我们的组合启发式方法非常有效且具有竞争力,在大多数测试问题上均优于基准方法。

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