An ant colony optimization for single-machine tardiness scheduling with sequence-dependent setups
An ant colony optimization for single-machine tardiness scheduling with sequence-dependent setups
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DOI：
10.1016/j.cor.2005.07.020
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发表时间：
2007-07
期刊：
影响因子：
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通讯作者：
C. Liao;Hsiao-Chien Juan
中科院分区：
文献类型：
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作者：
C. Liao;Hsiao-Chien Juan
在许多现实世界的生产系统中，它需要一个显式的顺序相关的设置时间时，调度作业的考虑。在调度准则方面，加权拖期一直被认为是实际系统中最重要的调度准则之一。虽然序列相关的设置时间的加权拖期问题的重要性已被认识到，这个问题在调度文献中很少受到关注。在本文中，我们提出了一种蚁群优化（ACO）算法在单机环境中这样的问题。所提出的蚁群算法有几个特点，包括引入一个新的参数的初始信息素线索和调整的时机，应用本地搜索，等等。在基准问题实例上的实验结果表明，该算法优于现有算法。作为进一步的研究，该算法被应用到未加权版本的问题。实验结果表明，该算法与现有的性能最好的算法相比具有很强的竞争力。
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.