Optimal lateral transshipment policies for a two location inventory problem with multiple demand classes

• Published in: European journal of operational research Vol. 272; no. 2; pp. 481 - 495
• Main Authors: van Wijk, A.C.C., Adan, I.J.B.F., van Houtum, G.J.
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 16.01.2019
• Subjects: Inventory; Lateral transshipments; Multiple demand classes; Optimal policy; Spare parts; Lateral transshipments; Spare parts; Inventory; Optimal policy; Multiple demand classes
• ISSN: 0377-2217; 1872-6860
• DOI: 10.1016/j.ejor.2018.06.033

•The optimal lateral transshipment policy is a threshold type policy.•Two switching curves per demand class at each stockpoint describe this policy.•Under certain analytic conditions the optimal policy reduces to a simpler policy.•Given these conditions, either a complete pooling or a hold back policy is optimal.•The results also apply for substitution problems and ecommerce fulfillment problems. We consider an inventory model for spare parts with two stockpoints, providing repairable parts for a critical component of advanced technical systems. As downtime costs for these systems are expensive, ready–for–use spare parts are kept in stock to be able to quickly respond to a breakdown of a system. We allow for lateral transshipments of parts between the stockpoints upon a demand arrival. Each stockpoint faces demands from multiple demand classes. We are interested in the optimal lateral transshipment policy. There are three ways in which a demand can by satisfied: from own stock, via a lateral transshipment, or via an emergency procedure. Using stochastic dynamic programming, we characterize and prove the structure of the optimal policy, that is, the policy for satisfying the demands which minimizes the average operating costs of the system. This optimal policy is a threshold type policy, with state-dependent thresholds at each stockpoint for every demand class. We show a partial ordering in these thresholds in the demand classes. In addition, we derive conditions under which the so-called hold back and complete pooling policies are optimal, two policies that are often assumed in the literature. Furthermore, we study several model extensions which fit in the same modeling framework.