A Bi-objective Organ Transplant Supply Chain Network with Recipient Priority Considering Carbon Emission Under Uncertainty, a Case Study

As one of the most complicated and challenging networks among healthcare systems, organ transplant network necessitates an effective supply chain design. In this article, a bi-objective mixed integer nonlinear programming (MINLP) location-allocation model is proposed to design network, with objectives minimizing overall costs (including strategical operational costs) number unsatisfied demands under uncertainty. The developed calculates optimum facilities be established equipped for each organ, flows between them, optimal allocation cold vehicles, which combination similar works in context resource as novelties paper. Moreover, preciousness human life policy allocating organs. Hence, study, high-risk recipients, who are more likely die case unmet demand, prioritized above low-risk ones prevent mortality much possible. This article also takes transportation constraints into account effort minimize carbon emissions, environmental concerns present day. Numerical experiments demonstrate applicability model, study presented compute solutions methodology. Finally, various sensitivity analyses performed provide managerial insights.