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A genetic algorithm for the hybrid flow shop scheduling with unrelated machines and machine eligibility

机译:具有不相关机器和机器资格的混合流水车间调度的遗传算法

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This paper presents a genetic algorithm to solve the hybrid flow shop scheduling problem to minimize the total tardiness. Practical assumptions as unrelated machines and machine eligibility are considered. The proposed algorithm incorporates a new decoding method developed for total tardiness objective, which is able to obtain tight schedule meanwhile guarantee the influence of the chromosome on the schedule. The proposed algorithm has been calibrated with a full factorial design of experiment, and compared to several calibrated state-of-art algorithms on 450 instances with different size and correlation patterns of operation processing time. The results validate the effectiveness of the proposed algorithm. (C) 2018 Elsevier Ltd. All rights reserved.
机译:本文提出了一种遗传算法来解决混合流水车间调度问题,以最大限度地减少总拖延。考虑不相关机器和机器资格的实际假设。该算法结合了针对总拖尾率目标开发的一种新的解码方法,该算法能够获得紧凑的调度,同时保证染色体对调度的影响。所提出的算法已通过完整的因子设计实验进行了校准,并与450种具有不同大小和相关运算处理时间模式的实例上的几种经过校准的最新算法进行了比较。结果验证了所提算法的有效性。 (C)2018 Elsevier Ltd.保留所有权利。

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