A stochastic network model for ordering analysis in multi-stage supply chain systems

In this paper we consider the ordering problem in demand driven multi-stage supply chain system. Although ordering decisions are made independently at different supply chain levels which involve manufactures, wholesalers, retailers and customers, the economic performance of ordering policies of supply chain members are heavily interdependent due to the supply–demand relationship among them. Based on the graphical evaluation and review technique, we first present a novel stochastic network mathematical model for order and cost distribution analysis. Further, to investigate the effects of different sub-orders on total system order and the impact of ordering cost on supply chain economic performance, sensitivity analysis models for order fluctuations and ordering cost changes are developed respectively. Finally, a detailed simulation is presented to promote a better understanding of the model approach. The models and algorithms are stylized; however, they are applicable to complex supply chains. The strategy parameters in simulation are presented for various ordering policy settings. This leads to a decision support system for the multi-stage supply chain under various ordering policy scenarios, and will be helpful in identifying the key links in ordering networks and for designing effective strategies to improve supply chain performance.