Stochastic mixed-integer programming for a spare parts inventory management problem

The German Armed Forces provide an operation contingent to support the North Atlantic Treaty Organization (NATO) Response Force (NRF). To fulfill a mission, NRF operates number of technical systems, mostly vehicles. Each system is composed several parts which might fail over time, and it can only be used again in mission if all broken are replaced. For short deployments (e.g., one month), troops bring with them tightly constrained “warehouse” spare parts. ensure optimal use space, we present two-stage stochastic programming model where first stage chosen, then failures occur at random, second assigned systems. We carry out scenario-based approach, simulated by Monte-Carlo approach. demonstrate that resulting mixed-integer linear program solved using standard numerical solvers. Using real-world input data provided data, analyze sensitivity solutions respect size warehouse, service level, scenarios, compare our approach simpler, doctrine based warehousing strategies.