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首页> 外文期刊>International Journal of Production Research >A hybrid differential evolution and estimation of distribution algorithm based on neighbourhood search for job shop scheduling problems
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A hybrid differential evolution and estimation of distribution algorithm based on neighbourhood search for job shop scheduling problems

机译：基于邻域搜索的作业车间调度问题的混合差分进化与分布估计算法

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摘要

Job shop scheduling problem (JSSP) is a typical NP-hard problem. In order to improve the solving efficiency for JSSP, a hybrid differential evolution and estimation of distribution algorithm based on neighbourhood search is proposed in this paper, which combines the merits of Estimation of distribution algorithm and Differential evolution (DE). Meanwhile, to strengthen the searching ability of the proposed algorithm, a chaotic strategy is introduced to update the parameters of DE. Two mutation operators are adopted. A neighbourhood search (NS) algorithm based on blocks on critical path is used to further improve the solution quality. Finally, the parametric sensitivity of the proposed algorithm has been analysed based on the Taguchi method of design of experiment. The proposed algorithm was tested through a set of typical benchmark problems of JSSP. The results demonstrated the effectiveness of the proposed algorithm for solving JSSP.
机译：作业车间调度问题（JSSP）是典型的NP难题。为了提高JSSP的求解效率，提出了一种基于邻域搜索的混合差分进化和分布估计算法，结合了分布估计算法和差分进化算法（DE）的优点。同时，为了增强算法的搜索能力，引入了混沌策略来更新DE的参数。采用两个变异算子。基于关键路径上的块的邻域搜索（NS）算法用于进一步提高解决方案质量。最后，基于实验设计的田口方法对所提算法的参数敏感性进行了分析。通过一组典型的JSSP基准测试问题对提出的算法进行了测试。结果证明了所提出的算法解决JSSP的有效性。

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