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首页> 外文期刊>International journal of production economics >A branch-and-bound algorithm with Lagrangian relaxation to minimize total tardiness on identical parallel machines
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A branch-and-bound algorithm with Lagrangian relaxation to minimize total tardiness on identical parallel machines

机译:具有拉格朗日松弛的分支定界算法,可最大程度减少相同并行机上的总拖延

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摘要

The purpose of this paper is to propose a new branch-and-bound algorithm for a class of scheduling problems to minimize total tardiness on identical parallel machines. In this algorithm, the Lagrangian relaxation technique is applied to obtain a tight lower bound. In addition, the job dominance conditions for the single machine total tardiness problem are utilized for both restricting branches and improving the lower bound. As will be shown by computational experiments, instances with up to 25 jobs and with any number of machines are optimally solved by the proposed algorithm.
机译:本文的目的是针对一类调度问题提出一种新的分支定界算法,以最大程度减少相同并行机上的总拖延时间。在该算法中,应用了拉格朗日松弛技术来获得严格的下界。此外,针对单个机器总拖延问题的作业主导条件被用于限制分支和改善下限。正如计算实验所显示的那样,所提出的算法可以最佳地解决具有最多25个作业和任意数量机器的实例。

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