Reliable blood supply chain network design with facility disruption: A real-world application

The blood supply of hospitals in disasters is a crucial issue in supply chain management. In this paper, a dynamic robust location-allocation model is presented for designing a blood supply chain network under facility disruption risks and uncertainty in a disaster situation. A scenario-based robust approach is adapted to the model to tackle the inherent uncertainty of the problem, such as a great deal of a periodic variation in demands and facilities disruptions. It is considered that the effect of disruption in facilities depends on the initial investment level for opening them, which are affected by the allocated budget. The usage of the model is implemented by a real-world case example that addresses the demand and disruption probability as uncertain parameters. For large-scale problems, two meta-heuristic algorithms, namely the self-adaptive imperialist competitive algorithm and invasive weed optimization, are presented to solve the model. Furthermore, several numerical examples of managerial insights are evaluated.