Research on Supply Chain Resilience Network Design Based on Stochastic Programming in Emergency Events

In the context of uncertain demand and considering the scenario where a sudden event causes disruptions at the main supplier and distribution center, the problem of the supply chain network design with the objectives of enhancing resilience and minimizing total costs is studied. Research is conducted on the optimal supply chain network design problem with different combinations of four resilience measures: multi-sourcing, emergency supply, direct delivery to stores, and retailer emergency inventory. The model is solved using two-stage stochastic programming and the Sample Average Approximation (SAA). Sensitivity analysis is performed on the optimal results of resilient supply chain network design under different degrees of disruptions at the main supplier and distribution center, changes in market size, and maximum processing capacity changes of the retailer. Finally, through comparative analysis, the optimal strategies for resilient supply chain network design are determined.