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Minimizing weighted earliness-tardiness on parallel machines using hybrid metaheuristics

机译:使用混合元启发式算法最大程度地减少并行计算机上的加权早迟

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We consider the problem of scheduling a set of jobs on a set of identical parallel machines where the objective is to minimize the total weighted earliness and tardiness penalties with respect to a common due date. We propose a hybrid heuristic algorithm for constructing good solutions, combining priority rules for assigning jobs to machines and a local search with exact procedures for solving the one-machine subproblems. These solutions are then used in two metaheuristic frameworks, Path Relinking and Scatter Search, to obtain high quality solutions for the problem. The algorithms are tested on a large number of test instances to assess the efficiency of the proposed strategies. The results show that our algorithms consistently outperform the best reported results for this problem.
机译:我们考虑在一组相同的并行计算机上调度一组作业的问题,其目的是最大程度地减少相对于共同到期日的总加权提前和拖延罚款。我们提出了一种混合启发式算法,用于构造良好的解决方案,将用于将作业分配给机器的优先级规则和本地搜索与用于解决单机子问题的确切过程相结合。然后,将这些解决方案用于两个元启发式框架(路径重新链接和分散搜索)中,以获取针对该问题的高质量解决方案。在大量测试实例上对算法进行了测试,以评估所提出策略的效率。结果表明,对于该问题,我们的算法始终优于最佳报告结果。

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