Development of risk based dynamic backorder replenishment planning framework using Bayesian Belief Network

Due to the rapid changes in circumstances of cooperates such as globalization, technical innovation and competition, inter-dependence among cooperates which compose supply chain has been intensified. This make cooperates be exposed to various risk and even a small uncertainty can disrupt the balance of whole supply chain. Therefore, in this paper, the framework to develop alternative backorder replenishment plan to minimize the total replenishment cost and expected risk cost has been devised. In order to model the relationship between risks and risk propagation, Bayesian Belief Network has been applied. Moreover, with the fast heuristic algorithm, breath first search and elementary stepwise system based reverse Dijkstra, the alternative backorder replenishment plan can be established. The numerical example shows how to apply the proposed framework and make dynamic backorder replenishment plan considering impact of risk. 2011 Elsevier Ltd. All rights reserved.