Analysis of Tailored Base-Surge Policies in Dual Sourcing Inventory Systems

Abstract

We study a model of a firm managing its inventory of a single product by sourcing supplies from two supply sources, a regular supplier who offers a lower unit cost and a longer lead time than a second, emergency, supplier. A practically implementable policy for such a firm is a Tailored Base-Surge (TBS) Policy (Allon and Van Mieghem, 2010) to manage its inventory: Under this policy, the firm procures a constant quantity from the regular supplier in every period and dynamically makes procurement decisions for the emergency supplier. Allon and Van Mieghem describe this practice as using the regular supplier to meet a base level of demand and the emergency supplier to manage demand surges, and they conjecture that this practice is most effective when the lead time difference between the two suppliers is large. We confirm these statements in two ways. First, we show the following analytical result: When demand is composed of a base demand random component plus a surge demand random component, which occurs with a certain small probability, the best TBS Policy is close to optimal (over all policies) in a well defined sense. Second, we also numerically investigate the cost-effectiveness of the best TBS policy on a test bed of problem instances. The emphasis of this investigation is the study of the effect of the lead time difference between the two suppliers. Our study reveals that the cost difference between the best TBS policy and the optimal policy decreases dramatically as the lead time of the regular supplier increases. On our test bed, this cost difference decreases from an average (over the test bed) of 21 % when the lead time from the regular supplier is two periods (the emergency supplier offers instant delivery) to 3.5 % when that lead time is seven periods.

Global Dual Sourcing and Order Smoothing: The Impact of Capacity and Lead Times

“…Scaled cost l to increased inventory holding costs compared to the dual-base-stock policies. The TBS policy improves as the lead time difference increases (as also shown by Janakiraman et al 2015).…”

“…This allows some mathematical tractability: Allon and Van Mieghem (2010) develop an analytical Brownian model that is asymptotically optimal for high sourcing volumes. Janakiraman et al (2015) show that the TBS policy is optimal when demand comes from a two-point distribution and when the probability of the smaller (base) demand is sufficiently large. They also show that TBS performance, relative to the optimal policy, improves as the lead time of the regular source increases.…”

“…Management Science 61(9), pp. 2080-2099, © 2015 Optimal dual-sourcing policies are, in general, highly complex. Therefore, various heuristic policies are proposed in the literature.…”

“…The TBS policy requires the evaluation of a G/D/1 queue, where the interarrival time has the per-period demand distribution and the processing time is the fixed order size from the global source. For certain choices of the demand distribution, this is a tractable problem (as shown by Janakiraman et al 2015), but for general demand distributions we need to rely on a simulation analysis to optimize the target base-stock and capacity levels.…”

Building Supply Chain Resilience through Virtual Stockpile Pooling

“…(), and Janakiraman et al. (). Different from the focus of these studies, the current study concerns another lever—inventory stockpiling.…”