A possibilistic multi-objective optimization model for sustainable blood supply chain with vehicle routing and transshipment

This paper presents a possibilistic optimization model for the blood supply chain, addressing uncertainty and the pillars of sustainability: economy, environment, and society. The research encompasses multiple levels, including donor locations, blood centers, hospitals, and disposal centers. It employs a vehicle routing approach to determine the optimal route for bloodmobiles when collecting blood from donors. Additionally, the study incorporates a transshipment policy between blood centers to minimize shortages of blood products. The optimization model developed herein accounts for carbon emissions resulting from the production, inventory, and distribution processes of blood products across the supply chain. To tackle uncertainty, this study utilizes a fuzzy programming approach with a multi-objective function aimed at minimizing the overall costs of the blood supply chain, reducing carbon emissions, and maximizing job opportunities at blood centers. The optimal solution for the blood supply chain model is derived using the Torabi-Hassini (TH) Method, which considers compensation factors and the importance weights determined by decision-makers. The model was solved using the LINGO Ver 15.0. The sensitivity analysis result reveals that the compensation factor significantly impacts both the total supply chain costs and carbon emissions. Notably, the highest levels of carbon emissions are generated during the transshipment process of blood products.