OPTIMAL ORDERING IN A DUAL‐SUPPLIER SYSTEM WITH DEMAND FORECAST UPDATES

Abstract

We study how an updated demand forecast affects a manufacturer's choice in ordering raw materials. With demand forecast updates, we develop a model where raw materials are ordered from two suppliers—one fast but expensive and the other cheap but slow—and further provide an explicit solution to the resulting dynamic optimization problem. Under some mild conditions, we demonstrate that the cost function is convex and twice‐differentiable with respect to order quantity. With this model, we are able to evaluate the benefit of demand information updating which leads to the identification of directions for further improvement. We further demonstrate that the model applies to multiple‐period problems provided that some demand regularity conditions are satisfied. Data collected from a manufacturer support the structure and conclusion of the model. Although the model is described in the context of in‐bound logistics, it can be applied to production and out‐bound logistics decisions as well.