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An ant colony optimization for single-machine tardiness scheduling with sequence-dependent setups

机译:基于序列的设置的单机延迟调度的蚁群优化

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摘要

In many real-world production systems, it requires an explicit consideration of sequence-dependent setup times when scheduling jobs. As for the scheduling criterion, the weighted tardiness is always regarded as one of the most important criteria in practical systems. While the importance of the weighted tardiness problem with sequence-dependent setup times has been recognized, the problem has received little attention in the scheduling literature. In this paper, we present an ant colony optimization (ACO) algorithm for such a problem in a single-machine environment. The proposed ACO algorithm has several features, including introducing a new parameter for the initial pheromone trail and adjusting the timing of applying local search, among others. The proposed algorithm is experimented on the benchmark problem instances and shows its advantage over existing algorithms. As a further investigation, the algorithm is applied to the unweighted version of the problem. Experimental results show that it is very competitive with the existing best-performing algorithms.
机译:在许多实际的生产系统中,在计划作业时需要明确考虑与序列相关的设置时间。至于调度标准,加权迟到总是被认为是实际系统中最重要的标准之一。虽然已经认识到加权拖延问题与序列相关的建立时间的重要性,但是在调度文献中该问题很少受到关注。在本文中,我们提出了针对单机环境中此类问题的蚁群优化(ACO)算法。提出的ACO算法具有多个功能,其中包括为初始信息素跟踪引入新参数以及调整应用本地搜索的时机等。提出的算法在基准问题实例上进行了实验,显示了其优于现有算法的优势。作为进一步的研究,将该算法应用于问题的未加权版本。实验结果表明,与现有的最佳性能算法相比,它具有很大的竞争力。

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