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NEH-based heuristics for the permutation flowshop scheduling problem to minimise total tardiness

机译:基于NEH的置换Flowshop调度问题的启发式算法,可将总拖延率降至最低

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Since Johnson's seminal paper in 1954, scheduling jobs in a permutation flowshop has been receiving the attention of hundreds of practitioners and researchers, being one of the most studied topics in the Operations Research literature. Among the different objectives that can be considered, minimising the total tardiness (i.e. the sum of the surplus of the completion time of each job over its due date) is regarded as a key objective for manufacturing companies, as it entails the fulfilment of the due dates committed to customers. Since this problem is known to be NP-hard, most research has focused on proposing approximate procedures to solve it in reasonable computation times. Particularly, several constructive heuristics have been proposed, with NEHedd being the most efficient one, serving also to provide an initial solution for more elaborate approximate procedures. In this paper, we first analyse in detail the decision problem depending on the generation of the due dates of the jobs, and discuss the similarities with different related decision problems. In addition, for the most characteristic tardiness scenario, the analysis shows that a huge number of ties appear during the construction of the solutions done by the NEHedd heuristic, and that wisely breaking the ties greatly influences the quality of the final solution. Since no tie-breaking mechanism has been designed for this heuristic up to now, we propose several mechanisms that are exhaustively tested. The results show that some of them outperform the original NEHedd by about 25% while keeping the same computational requirements. (C) 2015 Elsevier Ltd. All rights reserved.
机译:自从约翰逊(Johnson)在1954年发表开创性论文以来,在排列流程车间安排作业一直受到数百名从业人员和研究人员的关注,这是运筹学文献中研究最多的主题之一。在可以考虑的不同目标中,最大程度地减少总拖延时间(即,每个工作在完成日期之前的剩余时间的总和)是制造公司的主要目标,因为这需要履行应有的义务。致力于客户的日期。由于已知此问题是NP难题,因此大多数研究都集中在提出近似过程以在合理的计算时间内解决它。特别是,已经提出了几种建设性的启发式方法,其中NEHedd是最有效的启发式方法,还可以为更精细的近似过程提供初始解决方案。在本文中,我们首先根据工作到期日的生成来详细分析决策问题,并讨论与不同相关决策问题的相似性。此外,对于最典型的拖后情况,分析表明,在由NEHedd启发式方法构造解决方案的过程中会出现大量联系,而明智地打破联系会极大地影响最终解决方案的质量。到目前为止,由于尚未针对这种启发式设计任何打破常规的机制,因此我们提出了几种经过详尽测试的机制。结果表明,其中一些在保持相同计算要求的情况下,比原始NEHedd的性能高出约25%。 (C)2015 Elsevier Ltd.保留所有权利。

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