Optimization of reliability for a hierarchical facility location problem under disaster relief situations by a chance-constrained programming and robust optimization

Despite the frequent use of hierarchical facility location decisions for public facilities such as hospitals and schools and their important role in positioning relief facilities effectively, few studies have examined the optimized positioning of such facilities under uncertainty, which is imposed by the nature of a disaster. In this article, we present a hierarchical facility location model in a supply chain of disaster relief under uncertainty in order to schedule the customers’ services. In this model, we consider a positive probability for roadways to become closed for relief operations when a disaster occurs. In this network, a higher level relief facility offers all services provided by a minimum relief facility. Since the aim of this model is to rapidly provide the appropriate emergency supplies to the affected villages, we optimize the reliability of the network by constructing more roads and infrastructure between all villages and relief centers. For this purpose, a robust optimization and chance-constrained programming method was applied. Finally, the hybridization of the genetic algorithm, simulated annealing and an optimization technique will be introduced to solve the model efficiently.