Synchronization of donor utility and qualitative measures to optimize a blood supply chain under uncertainty

In today's world, ensuring both easy access to healthcare services and cost-effectiveness is paramount. Addressing this need, our paper introduces a novel three-phase multi-attribute two-stage stochastic-robust approach to design a multi-echelon blood supply chain, integrating service-oriented objectives with financial considerations. This innovative model tackles a multi-objective, multi-product problem over a planning horizon. The first objective function is to minimize the total network cost for quantitative attributes, while the second objective aims to preserve blood freshness. The third objective focuses on maximizing blood donors' utility, enhancing the active donor pool, and mitigating potential shortages. We employ the interactive bundle-based method for nondifferentiable multi objective optimization (NIMBUS) to convert these objectives into scalar-valued optimization problems under various scenarios. To demonstrate the practical applicability, we apply it to a real-world case study, highlighting its wide applicability of the proposed model and its solution in real-world situations. Sensitivity analyses on critical parameters further validate the model's robustness and solution efficacy, underscoring its potential to revolutionize blood supply chain management.