Modeling location–allocation of emergency medical service stations and ambulance routing problems considering the variability of events and recurrent traffic congestion: A real case study

One of the most important and common criteria for evaluating the emergency medical systems is the response time, which is a function of the availability of an ambulance at the time of the request and the time that it takes for the ambulance to arrive at the call location. In this study, an optimization model is proposed to deal with the problem of the emergency medical service stations’ location and ambulance allocation. In order to capture the impacts of uncertainty in the network and obtain more realistic results, it is assumed that medical aid demands from any location in the city at any time slot of the day have a probabilistic distribution. In addition, to consider the traffic fluctuations in the modeling process, it is assumed that the arrival time to the request location is a time dependent variable. To deal with the complexity of the proposed approach and find optimal solutions in a reasonable execution time, some heuristic algorithms are suggested to solve the ambulance routing problem and the proposed non-linear integer model. To show the applicability of proposed models and algorithms in large-scale networks, the models and algorithms have been applied to the emergency medical system of the city of Isfahan, Iran. Three different scenarios are defined to improve the performance of the emergency medical services in Isfahan. The results show that relocating emergency medical service stations and reallocating ambulances will lead to significant improvements in both response time and coverage area in Isfahan.

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