Joint optimization of location and allocation for spare parts depots under ($ r, Q $) inventory policy

Abstract

<p>The ability to replace failed spare parts in time directly affects the supportability level of equipment systems. The selection of spare parts' depot locations, inventory mode, and allocation are often separate and independent operations. However, in these situations, the total supply cost is usually relatively high with the consideration of spare parts shortage and maintenance delays. Therefore, this article dealt with a depot location-inventory-allocation problem based on the $ (r, Q) $ inventory method and analyzed a combined network of centralized spare part depot locations, inventory, and allocation. Meanwhile, considering the convenience and speed of spare parts transportation brought about by the improvement of transportation capacity, a network is proposed to adopt a centralized storage and point-to-point allocation strategy for parts replacement, which reduces supportability costs without affecting supply efficiency. An optimization model has been developed that reduces the overall cost of support, including inventory, construction, transportation, and logistics. Three equipment support efficiency metrics were used as constraints in this model to assess the location of open depots: selection availability, fill rate, and predicted downtime. Additionally, due to the knowledge asymmetry, there are some shortage issues which always lead to extra expenditure. The model also introduces uncertain distribution to demand measurement and adopts a genetic algorithm for model solving. Ultimately, a numerical instance was developed so as to verify our results.</p>