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首页> 外文会议>2010 International Conference on Logistics Systems and Intelligent Management >A tabu search heuristic to solve the scheduling problem for a batch-processing machine with non-identical job sizes
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A tabu search heuristic to solve the scheduling problem for a batch-processing machine with non-identical job sizes

机译：禁忌搜索启发式方法，用于解决作业大小不相同的批处理机器的调度问题

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摘要

A scheduling problem for the batch-processing machine with non-identical job sizes is investigated. The objective is to minimize the makespan. The problem has been proved to be NP-hard. Hence, a tabu search heuristic is proposed to solve it approximately. Besides the basic neighborhoods, three variable depth neighborhoods which are explored by the filter-and-fan method are proposed and used in the tabu search process for further improvement. The larger neighborhood can be obtained by adjusting the depth of search dynamically in the filter-and-fan method. A group of random instances are generated to test the effectiveness of the heuristic we proposed. The experimental results show that the heuristic can obtain the optimal solutions for most of the instances with small scales. And for all the instances with large scales, the heuristic significantly outperform the standard commercial solver both on run time and quality of solution.
机译：研究了工作量不相同的批处理机器的调度问题。目的是使制造期最小化。该问题已被证明是NP难题的。因此，提出了禁忌搜索启发式算法来对其进行近似求解。除了基本邻域外，还提出了三个通过过滤和扇动方法探索的可变深度邻域，并将其用于禁忌搜索过程中以进一步改进。通过使用“过滤并扇动”方法动态调整搜索深度，可以获得较大的邻域。生成一组随机实例来测试我们提出的启发式算法的有效性。实验结果表明，启发式算法可以为大多数小规模实例获得最优解。对于所有规模较大的实例，启发式方法在运行时间和解决方案质量上均明显优于标准的商用求解器。

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