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Permutation flowshops in group scheduling with sequence-dependent setup times

机译:组调度中的置换流程,具有与序列相关的建立时间

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This paper focuses on the flow shop sequence dependent group scheduling (FSDGS) problem with minimisation of total completion time as the criterion (Fm|f_(mls), prmu, S_(plk)|∑C_j). The research problem is formulated in form of two different mixed integer linear programming (MILP) models. Comparing with the latest MILP model for the proposed problem in the literature, the complexity size of the proposed models are significantly reduced. One of the proposed mathematical models is so effective that even medium-sized instances (problems up to 60 jobs in all groups) are solved to optimality in a reasonable amount of time. Moreover, a metaheuristic hybridising genetic and simulated annealing algorithm, called GSA, is proposed to solve the problems heuristically. All the results and analyses show the high performance of the proposed mathematical models as well as the proposed metaheuristic algorithm compared to the available ones in literature.
机译:本文以流水车间序列相关的组调度(FSDGS)问题为重点,以总完成时间最小化为准则(Fm | f_(mls),prmu,S_(plk)| ∑C_j)。研究问题以两种不同的混合整数线性规划(MILP)模型的形式提出。与文献中针对提出的问题的最新MILP模型相比,提出的模型的复杂性大小显着降低。所提出的数学模型之一如此有效,以至于在合理的时间内,即使中等大小的实例(所有组中最多可解决60个工作)也能达到最优。此外,提出了一种启发式混合遗传和模拟退火算法GSA,以启发式地解决该问题。所有的结果和分析表明,与文献中的可用数学模型相比,所提出的数学模型以及所提出的元启发式算法具有较高的性能。

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