A Location-Allocation Problem of Emergency Facilities Considering Multi-Resources Under Uncertainty

Due to the suddenness of disasters and the presence of multiple uncontrollable factors, such as the number of casualties, the availability of emergency relief supplies, and the responsiveness of hospitals, it is crucial to ensure the timely delivery of emergency relief supplies and the promptness of medical services under conditions of significant uncertainty. Therefore, this paper, based on the myriad uncertainties caused by disasters, adopts a priori optimization methods, incorporates multiple random variables and discrete stochastic scenarios to enhance model reliability, and proposes a two-stage stochastic model for the location-allocation of emergency facilities. This model is further transformed into an equivalent deterministic model based on discrete scenarios, and integrates queueing theory to calculate the casualties' waiting penalty cost. For solving the model, this paper first employs an outer approximation method to simplify the nonlinear parts of the model, facilitating the resolution of small-scale problems; for large-scale problems, a Kernel search algorithm is proposed, enhanced by a sorting algorithm. Finally, the effectiveness of the model and algorithms is validated through test instances.