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Parallel machine scheduling problem with ready times, due times and sequence-dependent setup times using meta-heuristic algorithms

机译:使用就绪启发式算法的具有准备时间,到期时间和与序列相关的设置时间的并行机器调度问题

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摘要

This article considers a parallel machine scheduling problem with ready times, due times and sequence-dependent setup times. The objective of this problem is to determine the allocation policy of jobs and the scheduling policy of machines to minimize the weighted sum of setup times, delay times and tardy times. A mathematical model for optimal solution is derived. An in-depth analysis of the model shows that it is very complicated and difficult to obtain optimal solutions as the problem size becomes large. Therefore, two meta-heuristics, genetic algorithm (GA) and a new population-based evolutionary meta-heuristic called self-evolution algorithm (SEA), are proposed. The performances of the meta-heuristic algorithms are evaluated through comparison with optimal solutions using several randomly generated examples.View full textDownload full textKeywordsparallel machine scheduling, sequence-dependent setup times, meta-heuristicRelated var addthis_config = { ui_cobrand: "Taylor & Francis Online", services_compact: "citeulike,netvibes,twitter,technorati,delicious,linkedin,facebook,stumbleupon,digg,google,more", pubid: "ra-4dff56cd6bb1830b" }; Add to shortlist Link Permalink http://dx.doi.org/10.1080/0305215X.2011.628388
机译:本文考虑了具有准备时间,到期时间和与序列相关的设置时间的并行机器调度问题。该问题的目的是确定作业的分配策略和机器的调度策略,以最小化设置时间,延迟时间和延迟时间的加权总和。推导了用于最佳解决方案的数学模型。对模型的深入分析表明,随着问题规模的增大,该模型非常复杂且难以获得最佳解决方案。因此,提出了两种元启发式算法,即遗传算法(GA)和一种新的基于种群的进化元启发式算法,称为自进化算法(SEA)。通过使用几个随机生成的示例与最佳解决方案进行比较,评估了元启发式算法的性能。查看全文下载全文关键字并行机器调度,与序列有关的设置时间,元启发式相关变量var addthis_config = {ui_cobrand:“泰勒和弗朗西斯在线” ,services_compact:“ citeulike,netvibes,twitter,technorati,美味,linkedin,facebook,stumbleupon,digg,google,更多”,发布号:“ ra-4dff56cd6bb1830b”};添加到候选列表链接永久链接http://dx.doi.org/10.1080/0305215X.2011.628388

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