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Efficient local search limitation strategy for single machine total weighted tardiness scheduling with sequence-dependent setup times

机译:具有顺序相关设置时间的单机总加权拖延调度的有效本地搜索限制策略

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This paper concerns the single machine total weighted tardiness scheduling with sequence-dependent setup times, usually referred as 1 vertical bar S-ij vertical bar Sigma w(j)T(j). In this NP-hard problem, each job has an associated processing time, due date and a weight. For each pair of jobs i and j, there may be a setup time before starting to process j in case this job is scheduled immediately after i. The objective is to determine a schedule that minimizes the total weighted tardiness, where the tardiness of a job is equal to its completion time minus its due date, in case the job is completely processed only after its due date, and is equal to zero otherwise. Due to its complexity, this problem is most commonly solved by heuristics. The aim of this work is to develop a simple yet effective limitation strategy that speeds up the local search procedure without a significant loss in the solution quality. Such strategy consists of a filtering mechanism that prevents unpromising moves to be evaluated. The proposed strategy has been embedded in a local search based metaheuristic from the literature and tested in classical benchmark instances. Computational experiments revealed that the limitation strategy enabled the metaheuristic to be extremely competitive when compared to other algorithms from the literature, since it allowed the use of a large number of neighborhood structures without a significant increase in the CPU time and, consequently, high quality solutions could be achieved in a matter of seconds. In addition, we analyzed the effectiveness of the proposed strategy in two other well-known metaheuristics. Further experiments were also carried out on benchmark instances of problem 1 vertical bar S-ij vertical bar Sigma T-j. (C) 2016 Elsevier Ltd. All rights reserved.
机译:本文涉及具有序列相关设置时间的单机总加权拖延调度,通常称为1竖线S-ij竖线Sigma w(j)T(j)。在这个NP难题中,每个作业都有相关的处理时间,到期日和权重。对于每对作业i和j,如果在i之后立即安排该作业,则在开始处理j之前可能会有一个设置时间。目的是确定一个计划,以使总加权拖延时间最小化,如果作业仅在其拖延日期之后才被完全处理,则该拖延时间等于其完成时间减去其到期日,否则为零。 。由于其复杂性,此问题最常通过启发式方法解决。这项工作的目的是开发一种简单而有效的限制策略,以加快本地搜索过程,而不会显着降低解决方案质量。此类策略由过滤机制组成,该机制可防止评估不可靠的举动。所提出的策略已嵌入文献中基于本地搜索的元启发式方法,并在经典基准实例中进行了测试。计算实验表明,与文献中的其他算法相比,限制策略使元启发式方法具有极强的竞争力,因为它允许使用大量的邻域结构,而不会显着增加CPU时间,因此提供了高质量的解决方案只需几秒钟即可完成。此外,我们在其他两个著名的元启发式方法中分析了所提出策略的有效性。还对问题1竖线S-ij竖线Sigma T-j的基准实例进行了进一步的实验。 (C)2016 Elsevier Ltd.保留所有权利。

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