Hybrid Fuzzy and Data-Driven Robust Optimization for Resilience and Sustainable Health Care Supply Chain with Vendor-Managed Inventory Approach

One of the problems that government managers deal with are medical inventory management in COVID-19 conditions. Based on this situation, best strategy for managing and reducing costs can be Vendor-Managed Inventory (VMI) policy recent decade. Therefore, a hybrid fuzzy data-driven robust optimization Resilience Sustainable Health Care Supply Chain (RSHCSC) VMI approach is appropriate improving system tackling uncertainty disruption situation. Three RSHCSC models suggested using stochastic programming approach. The first model average mean absolute function, second Conditional Value at Risk (CVaR), third Minimax model, final traditional model. Each proposed has advantages disadvantages depend conservative level decision-maker. Sensitivity analysis done essential parameters like cut, confidence level, resilience coefficient, size models. results show increasing robustification resiliency CVaR amount grows. function suitable decision-makers.