We study the integrated logistics network design and inventory stocking problem as characterized by the interdependency of the design and stocking decisions in service parts logistics. These two sets of decisions have been usually considered sequentially in practice, and the associated problems have been tackled separately in the research literature. The overall problem is typically further complicated due to time-based service constraints that provide lower limits for the percentages of demand satisfied within specified time windows. We introduce an optimization model that explicitly captures the interdependency between network design (location of facilities, and allocation of demands to facilities) and inventory stocking decisions (stock levels and their corresponding stochastic fill rates), and present computational results from our extensive experiments that investigate the effects of several factors including demand levels, time-based service levels, and costs. We show that the integrated approach can provide significant cost savings over the decoupled approach (solving the network design first and inventory stocking next), shifting the whole efficient frontier curve between cost and service level to superior regions. We also show that the decoupled and integrated approaches may generate totally different solutions, even in the number of located facilities and in their locations, magnifying the importance of considering inventory as part of the network design models.

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