This article proposes a novel design of a disaster relief blood supply chain network with multiple echelons and multiple products. It incorporates: (1) the blood donors’ behavior and preference for the selection of facilities where the blood donation takes place, (2) an estimating the quantity of the injured people under each disaster scenario, (3) the inherent uncertainty in input parameters and (4) the remaining capacity for satisfying the demand affected by the disruption in blood facilities (i.e., both blood collection and production centers). To incorporate the utility of blood collection facilities, a utility assessment approach, called Logit model, is developed, which measures the donors’ preference. The disrupted capacity and the number of injured people under each disaster scenario are estimated based on the disaster severity, the distance from the disaster (particularly earthquake) epicenter and the civil infrastructure. The uncertainty of parameters (e.g., cost parameters as well as blood supply and demand) along with the disruption in blood facilities are two unavoidable concerns of disaster relief blood supply chain planning. Accordingly, to handle the parameters under mixed uncertainty, a new approach which is two-stage stochastic-robust is utilized. Finally, using real data of a case study in Iran, the presented formulation and its solution approach are examined. The obtained results demonstrate that the related managers should be aware of blood donors’ behavior, injured people in disaster, and the effect of disruption in the blood supply chain network design. Moreover, when it comes to the uncertainty of parameters, the obtained results from the robust model overcome those of deterministic one. Finally, based on findings, applicable managerial insights are derived for the decision-makers in blood supply chain network design for disaster relief cases.
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Samani, M.R.G., Hosseini-Motlagh, S. A robust framework for designing blood network in disaster relief: a real-life case. Oper Res Int J (2020). https://doi.org/10.1007/s12351-020-00588-0
- Blood supply chain
- Logit model
- Disruption risk
- Mixed uncertainty