Abstract: In wartime, the spare parts warehouse or transport carrier may be attacked deliberately, and some storage and transportation capacity may be completely or partially lost, which leads to the interruption of spare parts supply system. The interruption risk of supply network is an uncertain parameter and difficult to be predicted and change dynamically. In view of the depth uncertainty of interruption risk, the diversification of wartime spare parts supply optimization objectives is considered. A joint optimization model of multi-objective location-allocation for wartime spare parts supply is constructed for the minimum cost of spare parts supply and the shortest lead time of supply. A corresponding robust optimization model is established based on the robust equivalent change of polyhedron uncertainty set. The meta-heuristic algorithms are used to obtain the non-dominate solution sets and the corresponding supply plans. The results show that the efficiency and reliability of spare parts supply network can be greatly improved by strengthening some key nodes. On the other hand, the optimal solution of the robust optimization model can guarantee the feasibility of the worst-case solution of spare parts supply, that is, the model has good robustness. Key

Key words: sparepartssupply, disruptionrisk, location-allocationproblem, multi-objectiveoptimization, robustoptimization