Managing a Hybrid RDC‐DC Inventory System

Abstract

In this study, we study a hybrid RDC‐DC serial inventory system where the regional distribution center (RDC) replenishes its stock from an outside supplier (OS), while the distribution center (DC) faces random demand and replenishes its stock from the RDC. Unlike in the traditional serial system, the DC itself can replenish its inventory from outside as well. We firstly derive structural properties for the optimal long‐run average cost and the optimal stationary policy by vanishing discount approach, and then propose two simple and easy‐to‐implement policies. The first policy, which we call the three‐index policy, combines the characteristics of the echelon‐base‐stock policy for the serial system (Clark and Scarf. 1960. Management Sci.6(4): 475–490) and the dual‐index policy for the dual‐sourcing system (Veeraraghavan and Scheller‐Wolf. 2008. Oper. Res.56(4): 850–864). We show that the order‐up‐to level of the DC from the RDC can be computed by a newsboy fractile. A simulation‐based optimization procedure for the policy is provided. We then develop the approximate linear programming (ALP) policy based on the three‐index policy and the multimodularity of the problem. This policy applies the linear programming approach to approximately solve the value function of the dynamic programming formulation. Numerical results show that both the three‐index policy and the ALP policy are comparable to the optimal policy computed via dynamic programming, and the latter performs slightly better. Moreover, the OS of the DC can draw considerable cost savings under both policies. We also conduct a numerical study with problem parameters calibrated using actual data from a consumer goods company in China to glen insights on the management of the system.