文章基本信息

标题：Multi-objective Robust Optimization Model for Spare Parts Supply in Wartime
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作者：Yadong Wang ; Quan Shi
期刊名称：Engineering Letters
印刷版ISSN：1816-093X
电子版ISSN：1816-0948
出版年度：2019
卷号：27
期号：4
页码：794-801
出版社：Newswood Ltd
摘要：High uncertainty is one of the challenges faced by wartime spare parts supply because of the diversity of combat scenarios, the fluctuation of spare parts demands and the supply risk. Considering the uncertainty of scenarios and such parameters, a robust optimization model of wartime spare parts supply is constructed. In the model, the shortest lead time and the minimum shortage costs are considered simultaneously, which is formulated as a multi-objective optimization problem. The adaptive penalty function method is used for the unconstrained processing. A multi-objective differential evolution algorithm with improved evolution strategy is used to solve the model. The results of the example show that, on the one hand, the improved evolution strategy improves the performance of the algorithm to some extent. On the other hand, the optimal solution of the robust optimization model can guarantee the feasible of wartime spare parts supply in the "worst case", that is, the model has a good robustness.
关键词：wartime; spare parts supply; uncertainty; robust optimization; multi-objective optimization