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首页> 外文期刊>RAIRO Operation Research >A BRANCH AND BOUND ALGORITHM TO MINIMIZE THE SINGLE MACHINE MAXIMUM TARDINESS PROBLEM UNDER EFFECTS OF LEARNING AND DETERIORATION WITH SETUP TIMES
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A BRANCH AND BOUND ALGORITHM TO MINIMIZE THE SINGLE MACHINE MAXIMUM TARDINESS PROBLEM UNDER EFFECTS OF LEARNING AND DETERIORATION WITH SETUP TIMES

机译:在设置时间的学习和破坏作用下最小化单机最大目标问题的分枝有界算法

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摘要

This paper sheds light on minimizing the maximum tardiness with processing and setup times under both learning effect and deterioration. In this paper, all the jobs have processing and setup times under effects of learning and deterioration. By the effects of learning and deterioration, we mean that the processing time of a job is defined by an increasing function of its execution start time and position in the sequence. We provide a branch and bound algorithm to minimize the maximum tardiness under effects of learning and deterioration with setup times. Computational experiments show that the proposed algorithm can solve instances up to 800 jobs in reasonable time.
机译:本文探讨了在学习效果和劣化情况下,通过最大程度地减少处理和设置时间的最大拖后感。在本文中,所有作业在学习和恶化的影响下都有处理和设置时间。通过学习和恶化的影响,我们的意思是,作业的处理时间由其执行开始时间和序列中位置的递增函数定义。我们提供了一种分支定界算法,以最大程度地减少学习和设置时间恶化所带来的拖后感。计算实验表明,该算法在合理的时间内可以解决多达800个工作实例。

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