A Joint Location–Allocation–Inventory Spare Part Optimization Model for Base-Level Support System with Uncertain Demands

This paper copes with a joint Location-Allocation-Inventory problem in three-echelon base-level spare part support system epistemic uncertainty uncertain demands of bases. The aim the is to propose an optimization model under theory minimize total cost, which integrates crucial characterizations inventory control decisions and location-allocation scheme arrangement periodic review order-up-to-S (T, S) policy. Uncertainty introduced this characterize uncertainty, where are treated as variables stockout loss represented by value-at-risk measurement. To solve original model, equivalent deterministic derived addressed improved bilevel genetic algorithm. Moreover, proposed models algorithm encoded into numerical examples for supply chain programming. results highlight applicability algorithm’s effectiveness approaching optimal solution compared traditional Sensitivity analyses further made impacts time capacity on different cost components.