A multi-objective analytical framework for sustainable blood supply chain optimization

Abstract

This study presents a multi-objective optimization model for blood supply chain (BSC) management, aiming to maximize total profit and fulfillment rate and minimize carbon emissions. The model is formulated as a mixed-integer linear program (MILP) and solved using the weighted sum method. The BSCM is structured as a multi-echelon network involving blood mobiles, local blood centers, regional blood banks (RBBs), hospitals, and healthcare facilities. Assumptions include deterministic demand and fixed blood shelf life. A case study in East Kalimantan, Indonesia, shows a total revenue of Indonesian Rupiah (IDR) of 13.07 billion and a total cost of IDR 8.58 billion, resulting in a profit of IDR 4.49 billion. The fulfillment rates for hospitals and healthcare facilities are 109.13 % and 154.57 %, respectively. Total emissions reach 203.94-kilogram CO₂ equivalent (kg CO₂e), mainly from production. Sensitivity analysis highlights the impact of demand, capacity, and pricing on supply chain performance. Furthermore, transshipment among RBBs plays a vital role in balancing inventory levels, though excessive transshipment may lead to increased costs and emissions.