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A hybrid biogeography-based optimization for the fuzzy flexible job-shop scheduling problem

机译:基于混合生物地理学的模糊柔性作业车间调度问题优化

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Biogeography-based optimization is a novel evolutionary algorithm which mimics the immigration and emigration of species among habitats. In this paper, the biogeography-based optimization is combined with some heuristics to construct an effective hybrid algorithm for solving the fuzzy flexible job-shop scheduling problem. First, path relinking technique is employed as migration operation to generate a new solution. Then, an insertion-based local search heuristic is introduced and embedded in the biogeography-based optimization to modify the mutation operator. Moreover, an efficient machine assignment rule is also proposed to decode the representation based on the operation sequence. Consequently, the exploration and exploitation abilities of the hybrid algorithm are enhanced and well balanced. Computational results and the comparisons with some existing algorithms are presented to show the effectiveness of the proposed hybrid scheme. (C) 2015 Elsevier B.V. All rights reserved.
机译:基于生物地理的优化是一种新颖的进化算法,可模拟栖息地之间物种的迁移和迁移。本文将基于生物地理学的优化方法与一些启发式方法相结合,构造出一种有效的混合算法来解决模糊柔性作业车间调度问题。首先,将路径重新链接技术用作迁移操作以生成新的解决方案。然后,引入了基于插入的局部搜索启发式方法,并将其嵌入基于生物地理的优化中以修改变异算子。此外,还提出了一种有效的机器分配规则,以根据操作顺序对表示进行解码。因此,混合算法的探索和开发能力得到了增强,并得到了很好的平衡。计算结果以及与现有算法的比较结果表明了该混合方案的有效性。 (C)2015 Elsevier B.V.保留所有权利。

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