Affiliations: Department of Equipment Command and Management, Army Engineering University of PLA, Shijiazhuang, China
Correspondence:
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Corresponding author. Quan Shi, Department of Equipment Command and Management, Army Engineering University of PLA, Shijiazhuang, China. Tel.: +86 18795428481; E-mail: xwzj0003@gmail.com.
Abstract: In order to solve the problem of multi-period material supply in emergency logistics network, a dynamic multi-objective optimization mathematical model with constraints is constructed. The model takes the minimum cost and the maximum fill rate of demands as the objectives, and takes the location of distribution centers and the allocation of material as the decision variables. A dynamic self-adaptive multi-objective differential evolution algorithm is proposed to solve the mathematical model, and the feasible non-dominated solutions of the model are obtained. In the improved algorithm, on the one hand, a new environment change detect operator and a new environment change response strategy are adopted so that the traditional static optimization algorithm can be used to solve the dynamic optimization problem. On the other hand, the improved algorithm adopts adaptive mutation strategy to improve the ability of global exploration and local exploitation. Case study shows that the improved strategy greatly improves the performance of the algorithm, and can solve the dynamic multi-objective optimization problem effectively.
