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Improving Branch-and-Price for Parallel Machine Scheduling

机译:提高并行机调度的分支价格

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In this paper we present a hybrid exact-heuristic method to improve a branch-and-price algorithm to solve the unrelated parallel machines with sequence-dependent setup times scheduling problem. As most of the computational time in the column generation (CG) process is spent in subproblems, two new heuristics to solve the subproblems are embedded in the branch-and-price (BP) framework with the aim to improve the efficiency of the process in obtaining optimal solutions. Computational results show that the proposed method improves a state-of-the-art BP algorithm from the literature, providing optimal solutions for large instances (e.g. 50 machines and 180 jobs) of the parallel machine scheduling problem with sequence dependent setup times, in significantly less time. One of the proposed approaches reduces, in average, to a half the time spent in the root of the branch-and-price tree and to a quarter the time spent in the full branch-and-price algorithm.
机译:在本文中,我们提出了一种混合精确启发式方法,以改进分支价格算法,以解决与序列相关的设置时间调度问题的无关并行机。由于列生成(CG)过程中的大部分计算时间都用在子问题上,因此在分支价格(BP)框架中嵌入了两种用于解决子问题的新启发式方法,目的是提高过程的效率。获得最佳解决方案。计算结果表明,所提出的方法从文献中改进了最新的BP算法,从而为大型实例(例如50台机器和180个作业)的并行机器调度问题提供了最优的解决方案,该问题具有与序列相关的建立时间,更短的时间。所提出的方法之一平均将花费在分支和价格树的根上的时间减少了一半,并减少了花费在整个分支和价格算法中的四分之一的时间。

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