Logistics network design with inventory stocking for low-demand parts: Modeling and optimization

This paper models, analyzes and develops solution techniques for a network design and inventory stocking problem. The proposed model captures important features of a real service part logistics system, namely time-based service level requirements, and stochastic demands satisfied by facilities operating with a one-for-one replenishment policy. In essence, along with usual decisions of location and allocation, the model considers stock levels and fill rates as decisions, varying across facilities to achieve system-wide target service levels. A variable substitution scheme is used to develop an equivalent convex model for an originally non-convex problem. An outer-approximation scheme is used to linearize the convex model. Exact solution schemes based on the linearized model are proposed and computationally less demanding lower and upper bounding techniques for the problem are devised. Results from extensive computational experiments on a variety of problem instances based on real-life industrial data show the effectiveness of the overall approach.