A novel robust model for location-allocation of healthcare facilities considering pre-disaster and post-disaster characteristics

Health care centers are one of the most important municipal facilities that are directly involved in providing personal and social health. In this paper, a new Robust Mathematical Modeling is simultaneously provided to locate and efficiently allocate healthcare facilities, including different service levels of medical care, concerning the characteristics in normal and disaster situations. Furthermore, to help victims and prevent overcrowding in hospitals and medical centers during disasters, the establishment of temporary and outpatient centers is allowed for emergency provision of basic services. Also, the possibility to send equipment and medical teams to these centers is considered in the proposed model. Since the considered problem is included as NP-Complete problems, to solve the problem, two metaheuristic algorithms, harmony search algorithm and hybrid Tabu search combined with variable neighborhood search algorithm, and a lower bound based on Lagrangian relaxation method are presented. Finally, to examine the proposed algorithms, a number of sample problems are randomly generated in small and large sizes and the results of exact solutions and the lower bound resulting from the Lagrangian relaxation method are evaluated and compared with the results of the meta-heuristic algorithms. The results show the good performance of the proposed algorithms.