Evaluating the importance of dynamic allocation and routing of rescuers in reducing response time

Due to delay in receiving emergency medical services, a high number of injured people and patients annually lose their lives. Determining the medical service area and correct routing of rescuing operation is influential on the reduction of rescuers’ response time. Changing the traffic flow leads to change of medical service area. Therefore, it is expected that by observing changing traffic, the service area of any hospital would be updated. Using the required hardware and software equipment, which observe traffic flow, would be pricey. In order to utilize such equipment, it is required to have information about the degree of effect of traffic dynamic changes on reducing the service time to the demand points. In this research, the allocation of medical center services using static traffic data was evaluated against the allocation with dynamic traffic data on different days and hours. Then, the influence of different regional areas from traffic changes was investigated. Genetic and particle swarm optimization meta-heuristic algorithms were used in the allocation of services, then the average access time (or response time) to all demand points and border points were investigated separately in the 5th district of Tehran. According to the results, the average response time to all demand points when using static traffic data was 13.4% more than the response time to the same points when using dynamic traffic data. Also, while allocation with static traffic data, the average response time to border points (checkpoints) was 34.2% equivalent to 69 seconds more than allocation with dynamic traffic data. These results reveal an increase in response time delay to border points when services allocation with static traffic data. In addition, in the afternoon hours of the day, which coincide with the increase in requests for assistance, the difference in response time to the demand points during service allocation with static and dynamic traffic data increased. The research results show the important role of dynamic allocation in service improvement.