Optimal policy structure characterization for a two-period dual-sourcing inventory control model with forecast updating


International Journal of Production Economics

November 2014, vol. 157, pp.238-249

Departments: Information Systems and Operations Management, GREGHEC (CNRS)

Keywords: Inventory control, Forecast updating, Dual supply, Short life-cycle products, Optimal solution

A proposed single-product, stochastic, two-period inventory control model combines demand forecast updating with the flexibility of two supply sources. Demand is modeled by two independent, random variables over a two-period selling season. At the beginning of the first period, two quantities are ordered using two different supply options: a local supplier who delivers the ordered quantity immediately and a second supplier who delivers the ordered quantity at the beginning of the second period. The local supplier charges a higher cost per ordered unit. The model considers an initial inventory, so the decision maker has an opportunity at the beginning of the first period to return part of the available inventory to the supplier (or sell it in a parallel market). At the end of the first period, any unsatisfied demand is backlogged to be satisfied in the next period. At the beginning of the second period, exogenous market information updates the second-period demand forecast. According to this updated forecast and the actual inventory level, an additional quantity is ordered using the local procurement source or another quantity is returned to the supplier (or sold in a parallel market). With a dynamic programming approach, this research exhibits the structure of the optimal policy, characterized by order-up-to and salvage-up-to levels. The findings provide the structure of the second-period conditional optimal policy and analytical insights that characterize the first-period optimal policy. Furthermore, a numerical study reveals the impact of information quality on the optimal policy and the trade-off between the two procurement options