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- Title
基于超启发式算法的备件供应网络结构优化.
- Authors
王亚东; 石全; 夏伟; 陈材
- Abstract
In order to improve the efficiency and effectiveness of spare parts supply by optimizing the structure of supply network, three kinds of network structures of spare parts supply, which are traditional forward supply network, emergency lateral supply network and closed-loop supply network considering maintenance, are studied. A multi-objective optimization model with the objectives of minimum supply cost and the shortest supply time and the constraints of satisfaction rate and inventory is proposed in this paper. A hyper-heuristic multi-objective evolutionary algorithm based on ordering choice function is proposed to solve models in different network structures. By comparing the proposed algorithm with other evolutionary algorithms on the ZDT benchmarks, the superiority of the proposed hyper heuristic algorithm in convergence and distribution is verified. The numerical example shows that, on the one hand, compared with the traditional forward supply network, the lateral and closed-loop supply network can improve the timeliness and economy of spare parts supply. On the other hand, the hyper heuristic algorithm is superior to other meta heuristic algorithms in solving the models.
- Subjects
SPARE parts; CONSTRAINT satisfaction; MAINTENANCE equipment; INVENTORIES; EVOLUTIONARY algorithms; HEURISTIC algorithms; EMERGENCIES
- Publication
Systems Engineering & Electronics, 2020, Vol 42, Issue 3, p620
- ISSN
1001-506X
- Publication type
Article
- DOI
10.3969/j.issn.1001-506X.2020.03.016