In this paper, a brief review of the recently developed blood supply chain (BSC) management studies is firstly presented. Then, a first-ever multi-objective robust BSC model is proposed, which is inspired by the need for an integrated approach towards improving the performance of BSC networks under uncertain conditions. The network efficiency by minimizing cost, adequacy by providing reliable and sufficient blood supply, and effectiveness by controlling blood freshness are aimed at the proposed model. A two-phase approach based on robust programming and an augmented epsilon-constraint method is devised to model the uncertainty in parameters and provides a single-objective counterpart of the original multi-objective robust model. We investigate a case to illustrate the real-world applicability of the problem. The research comes to an end by performing some sensitivity analyses on critical parameters, and the results imply the capability of the model and its solution technique.
