Multi-product expedited ordering with demand forecast updates

Abstract

This paper studies a purchasing problem with multiple products, resource constraints, demand forecast updates and expedited ordering. The retailer procures the initial quantities of multiple products before the selling season, which are restricted by limited resource, and the retailer can improve the demand forecasts through observing the initial sales. Based on the updated demand forecasts and inventories on hand, the retailer can place an expedited order at higher costs for products during the selling season, which is restricted by the minimum quantity of reordering. We analyze the retailer's optimal procurement policies by trading off between forecast reliability, procurement costs and resource availability. The bi-level programming is used to model the purchasing problem and the binary search solution method is developed for solving the optimal solution. We extend the proposed algorithm to the case with two resource constraints, and also replace the expedited ordering with option contract in the extended study. Numerical experiments are designed to show the value of expedited ordering with demand forecast updates and to obtain managerial insights in comparison with the model with the option contract.