The Impact of Forecasting Accuracy on Stochastic Periodic Inventory Routing Problem

The Inventory Routing Problem (IRP) is an underlying optimization problem for a warehouse replenishing multiple retailers to satisfy their demands while minimizing transportation and inventory costs within the system. Forecasting accuracy plays an important role in IRP, because the demands are stochastic and the planning is done for a longer horizon. The uncertainty level among the planning horizon makes it challenging for the decision makers to find the optimum level of products to be delivered to the retailers as well as the best routing system to reach them. In this paper we consider the impact of forecasting accuracy on the inventory and service level for a set of randomly dispersed retailers around a central warehouse in a distribution centre. We optimize the inventory levels and expected costs for each retailer for an illustrative example. The results will be simulated to compare the actual and expected outcomes of the model