Modeling Critical Resource Allocation and Sharing under Pandemic Situation

Abstract

During pandemics and epidemics, healthcare systems may respond quickly to massive increases in demand by establishing surge capacity in facilities. However, adding new resources may not be the most effective approach. Given the inherent uncertainty of demand during pandemics, this paper develops a stochastic optimization model designed to improve the allocation and sharing of critical resources. The objective is to enhance the responsiveness of healthcare systems to substantial surges in demand during pandemics. The model integrates warehouse selections for vendor-managed inventory (VMI), inventory policies, and delivery decisions to investigate a healthcare supply network configuration problem. This problem considers multiple sourcing, various products, multiple periods, and lateral transshipment. Numerical experiments are conducted to verify the advantage of the proposed stochastic model, which, despite its higher overall cost, demonstrates its superiority over the deterministic approach. The results further indicate that resource sharing can significantly improve the resilience of healthcare systems and enhance patients' access to care during pandemics.