A Recovery Model for Sudden Supply Delay with Demand Uncertainty and Safety Stock

Abstract

In this paper, a recovery model is developed for managing sudden supply delays that affect retailers' Economic Order Quantity (EOQ) model. For this, a mathematical model is developed that considers demand uncertainty and safety stock, and generates a recovery plan for a finite future period immediately after a sudden supply delay. Solving recovery problems involve high commercial software costs, and their solutions are complex. Therefore, an efficient heuristic solution is developed that generates the recovery plan after a sudden supply delay. An experiment is conducted to test the proposed approach. To assess the quality and consistency of solutions, the performance of the proposed heuristic is compared with the performance of the Generalized Reduced Gradient (GRG) method, which is widely applied in constrained mathematical programming. Several numerical examples are presented and a sensitivity analysis is performed to demonstrate the effects of various parameters on the performance of the heuristic method. The results show that safety stock plays an important role in recovery from sudden supply delays, and there is a trade-off between backorder and lost sales costs in the recovery plan.