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Minimizing makespan for the distributed hybrid flowshop scheduling problem with multiprocessor tasks

机译:使用多处理器任务最小化分布式混合Flowshop调度问题的makepan

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The trend of globalization has recently seen the study of distributed scheduling problems. This study attempts to solve the distributed hybrid flowshop scheduling problem with multiprocessor tasks, and is the first attempt to address this problem. To solve this strongly NP-hard problem, a mixed integer linear programming formulation and self-tuning iterated greedy (SIG) algorithm that incorporates an adaptive cocktail decoding mechanism are presented to minimize the makespan. Comprehensive computational results demonstrate that the proposed SIG algorithm is extremely efficient and effective. This paper successfully expands the research area of distributed scheduling problems. (C) 2017 Elsevier Ltd. All rights reserved.
机译:全球化的趋势最近已经看到了分布式调度问题的研究。这项研究试图解决具有多处理器任务的分布式混合Flowshop调度问题,并且是解决该问题的首次尝试。为了解决这个强烈的NP-hard问题,提出了一种混合整数线性规划公式和自校正迭代贪婪(SIG)算法,该算法结合了自适应鸡尾酒解码机制,以最大程度地缩短了制作时间。综合计算结果表明,所提出的SIG算法非常有效。本文成功地扩展了分布式调度问题的研究领域。 (C)2017 Elsevier Ltd.保留所有权利。

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