Bijan Elmi - Department of Industrial Management, Science and Research Branch, Islamic Azad University, Tehran, Iran
Naghi Shoja - Department of Mathematics, Firoozkooh Branch, Islamic Azad University, Firoozkooh, Iran
Abbas Toloie Ashlaghi - Department of Industrial Management, Science and Research Branch, Islamic Azad University, Tehran, Iran
Soleiman Iranzadeh - Department of Industrial Management, Tabriz Branch, Islamic Azad University, Tabriz, Iran

Background: The ability of ambulance centers to respond to emergency calls is an important factor in the recovery of patients' health. This study aimed to provide a model for the establishment of emergency relief in the road network in ۲۰۲۰ in East Azerbaijan province. Methods: This applied-descriptive and experimental research with an explanatory modelling approach used the comments of ۷۰ experts to run a model, which was based on the use of a metaheuristic (genetic) algorithm ,Simulation for the number of ambulances and the composition of the monitoring list simultaneously , objective and subjective data combined ,the agent and environmental variables, were determined and modelled through a meta-hybrid approach during the agent-based simulation and the metaheuristic algorithm. Results: To travel the initial structure for ۴۰ dangerous points and five stations, the initial time was equal to ۷۸۶۰ Minutes, which reached a number between ۲۷۰۰ and ۴۰۰۰ Minutes after genetic optimization, production of a new list, and the mutation of ambulances from one station to another. Conclusion: This type of optimization can be used to accelerate activities and reduce costs. Due to the dissimilar traffic of the areas, the ambulance does not arrive at dangerous points at equal times. The travel time of all dangerous points can be reduced by changing the location of points, moving forward or backwards depending on the conditions, customizing the features of ambulances and dangerous points, and combining the list of areas to find the best location for emergencies according to the interaction between agents, environmental constraints, and different behavioral features.

Algorithms; Computer Simulation; Emergency Service, Hospital; Workplace