期刊
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
卷 54, 期 4, 页码 1039-1060出版社
TAYLOR & FRANCIS LTD
DOI: 10.1080/00207543.2015.1041575
关键词
estimation of distribution algorithm; differential evolution algorithm; neighbourhood search; hybrid optimisation; job shop scheduling
资金
- National Natural Science Foundation of China [51365030]
- Postdoctoral Science Foundation of China [2012M521802, 2013T60889]
- Science Foundation for Distinguished Youth Scholars of Lanzhou University of Technology [J201405]
- Lanzhou Science Bureau project [2013-4-64]
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.
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