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Transshipment policies for systems with multiple retailers and two demand classes

Zümbül Atan (), Lawrence V. Snyder () and George R. Wilson ()
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Zümbül Atan: Eindhoven University of Technology
Lawrence V. Snyder: Lehigh University
George R. Wilson: Lehigh University

OR Spectrum: Quantitative Approaches in Management, 2018, vol. 40, issue 1, No 6, 159-186

Abstract: Abstract Many retailers discriminate among their customers based on their value to the firm. Instead of losing a customer due to this discrimination or lack of inventory, a retailer might prefer to place a transshipment request with other retailers to satisfy the customer’s demand. The system as a whole can benefit from this type of transshipments. In this paper, we study a problem of a centrally controlled system with multiple retailers. Each retailer serves two types of customers: high priority and low priority. Each retailer employs a rationing policy with a rationing level k in the context of a continuous-review (r, Q) inventory replenishment model. The overall policy is referred to as an (r, k, Q) policy. Retailers can transship items from either other retailers or a more expensive central depot. We propose an enumeration-based approximation to find the cost-minimizing policy parameters for the individual retailers and an approximation procedure to solve the combined rationing and transshipment problem. The latter relies on adjusting the demand arrival rates and the unit transshipment costs for both types of customers at all retailers. An extensive numerical study highlights the impact of transshipments on the retailers’ rationing policies. Without transshipment opportunities among each other, retailers set their policy parameters so that the resulting service levels are high for both types of customers. Allowing transshipments results in more aggressive rationing policies, and retailers with aggressive rationing policies benefit from the transshipments the most.

Keywords: Rationing; Transshipment; Approximation procedure (search for similar items in EconPapers)
Date: 2018
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