A ROBUST OPTIMIZATION APPROACH MODEL FOR A MULTI-VACCINE MULTI-ECHELON SUPPLY CHAIN

This research investigates a multi-product, multi-echelon and multi-period vaccine supply chain (SC) network model under uncertainty and quality inspection errors. The objective function seeks optimizing the total cost (economic cost) of the SC. Moreover, the proposed model is formulated as a Mixed Integer Linear Programming problem (MILP) under multiple sources of uncertain parameters including demand, inspection errors, vaccine waste generated in healthcare centers, and defective treatment rate of vaccine waste. To provide meaningful solutions which are robust against future fluctuation of parameters, the robust optimization approach is utilized to incorporate the decision maker's risk attitude under different type of uncertainty sets namely, box, polyhedral and combination of interval polyhedral. The performance of the proposed model is demonstrated through an illustrative example. The results show the effect of different types of uncertainties on the overall objective function. Managerial insights and research implications in terms of reverse vaccine SC is advised and future research directions are proposed.