| Summary: | Despite extensive research and efforts to optimize Emergency Medical Service (EMS) during the last four decades, there are still critical and fundamental challenges to study. Operational problems experienced during implementation of the proposed models result in the emergence of new concerns and the development of other models. This research examines the optimal location of emergency medical centers in order to offer faster and more efficient care. The purpose of this study is to offer a mathematical model for locating emergency medical centers with the goal of increasing both the quantity and quality of demand coverage. Then, by defining numerical examples, the behavior of the model is analyzed. The model is first solved in small dimensions using GAMS, and due to the np-hard nature of the model, it is then studied in large dimensions using a meta-heuristic algorithm, which uses a Genetic Algorithm (GA) in this paper. Finally, the graphs’ results are compared to each other. Our findings indicate that as the dimensions of the problem increase, GAMS loses its ability to solve the problem and the solution time by GA decreases compared to GAMS. Ultimately, in a numerical example, we used contour lines to analyze the data. EMS potential points follow these lines and serve as demand points. Given the model’s accuracy has been proven with various parameters, the proposed model can be used to both meet demand for emergency medical services and determine the optimal location of emergency medical care facilities.
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