AIRP: A heuristic algorithm for solving the unrelated parallel machine scheduling problem

L. P. Cota, Matheus Nohra Haddad, M. Souza, V. N. Coelho
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引用次数: 19

Abstract

This paper deals with the Unrelated Parallel Machine Scheduling Problem with Setup Times (UPMSPST). The objective is to minimize the makespan. In order to solve it, we propose a heuristic algorithm, based on Iterated Local Search (ILS), Variable Neighborhood Descent (VND) and Path Relinking (PR). In this algorithm, named AIRP, an initial solution is constructed using the Adaptive Shortest Processing Time method. This solution is refined by the ILS, having an adaptation of the VND as local search method. The PR method is applied as a strategy of intensification and diversification during the search. The algorithm was tested in instances of the literature envolving up to 150 jobs and 20 machines. The computational experiments show that the proposed algorithm outperforms an algorithm from the literature, both in terms of quality and variability of the final solution. In addition, the algorithm established new best solutions for more than 80,5% of the test problems in average.
求解不相关并行机调度问题的启发式算法
研究了具有设置时间的不相关并行机调度问题(UPMSPST)。目标是最小化完工时间。为了解决这一问题,我们提出了一种基于迭代局部搜索(ILS)、变邻域下降(VND)和路径重链接(PR)的启发式算法。在AIRP算法中,采用自适应最短处理时间法构造初始解。该方法在局部搜索方法的基础上进行了改进,将VND作为局部搜索方法进行了改进。在搜索过程中,将PR方法作为一种集约化和多样化的策略加以应用。该算法在涉及多达150个工作和20台机器的文献实例中进行了测试。计算实验表明,该算法在最终解的质量和可变性方面都优于文献中的算法。此外,该算法平均为超过80.5%的测试问题建立了新的最优解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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