A genetic algorithm for the unrelated parallel machine scheduling problem with sequence dependent setup times
A genetic algorithm for the unrelated parallel machine scheduling problem with sequence dependent setup times
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DOI：
10.1016/j.ejor.2011.01.011
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发表时间：
2011-06
期刊：
影响因子：
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通讯作者：
Eva Vallada;Rubén Ruiz
中科院分区：
文献类型：
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作者：
Eva Vallada;Rubén Ruiz
针对不相关的并行机器调度问题，考虑了与机器和作业顺序相关的设置时间，提出了一种遗传算法。该遗传算法包括快速局部搜索和局部搜索增强交叉算子。使用实验设计（DOE）方法进行大量校准后，获得了两个版本的算法。我们审查，评估和比较提出的算法与从文献中已知的最佳方法。我们还开发了一个小型和大型实例的基准来进行计算实验。经过详尽的计算和统计分析，我们可以得出结论，该方法在综合基准集实例中表现出优异的性能，克服了其他评估方法。
In this work a genetic algorithm is presented for the unrelated parallel machine scheduling problem in which machine and job sequence dependent setup times are considered. The proposed genetic algorithm includes a fast local search and a local search enhanced crossover operator. Two versions of the algorithm are obtained after extensive calibrations using the Design of Experiments (DOE) approach. We review, evaluate and compare the proposed algorithm against the best methods known from the literature. We also develop a benchmark of small and large instances to carry out the computational experiments. After an exhaustive computational and statistical analysis we can conclude that the proposed method shows an excellent performance overcoming the rest of the evaluated methods in a comprehensive benchmark set of instances.