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首页> 外文期刊>International Journal of Production Research >Ieta-raps For The Early/tardy Single Machine Scheduling Problem
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Ieta-raps For The Early/tardy Single Machine Scheduling Problem

机译：早期/迟到的单机调度问题的Ieta-raps

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This paper investigates a meta-heuristic solution approach to the early/ tardy single machine scheduling problem with common due date and sequence-dependent setup times. The objective of this problem is to minimise the total amount of earliness and tardiness of jobs that are assigned to a single machine. The popularity of just-in-time (JIT) and lean manufacturing scheduling approaches makes the minimisation of earliness and tardiness important and relevant. In this research the early/tardy problem is solved by Meta-RaPS (meta-heuristic for randomised priority search). Meta-RaPS is an iterative meta-heuristic which is a generic, high level strategy used to modify greedy algorithms based on the insertion of a random element. In this case a greedy heuristic, the shortest adjusted processing time, is modified by Meta-RaPS and the good solutions are improved by a local search algorithm. A comparison with the existing ETP solution procedures using well-known test problems shows Meta-RaPS produces better solutions in terms of percent difference from optimal. The results provide high quality solutions in reasonable computation time, demonstrating the effectiveness of the simple and practical framework of Meta-RaPS.
机译：本文研究了具有共同到期日和与序列有关的设置时间的早期/迟到单机调度问题的元启发式解决方案。该问题的目的是最大程度地减少分配给单个机器的作业的早期性和延误性。即时（JIT）和精益生产调度方法的普及使得尽早性和拖延性的最小化变得非常重要和相关。在这项研究中，早期/拖延问题是通过Meta-RaPS（针对随机优先级搜索的元启发式算法）解决的。 Meta-RaPS是一种迭代式元启发式算法，它是一种通用的高级策略，用于根据随机元素的插入来修改贪婪算法。在这种情况下，通过Meta-RaPS修改贪婪的启发式方法（最短的调整处理时间），并通过局部搜索算法改进好的解决方案。与使用已知测试问题的现有ETP解决方案过程进行的比较显示，Meta-RaPS在与最优值的百分比差异方面提供了更好的解决方案。结果在合理的计算时间内提供了高质量的解决方案，证明了简单实用的Meta-RaPS框架的有效性。

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