| Article ID: | iaor1998240 |
| Country: | Netherlands |
| Volume: | 75 |
| Issue: | 3 |
| Start Page Number: | 567 |
| End Page Number: | 581 |
| Publication Date: | Jun 1994 |
| Journal: | European Journal of Operational Research |
| Authors: | Repede John F., Bernardo John J. |
| Keywords: | artificial intelligence: decision support, location |
Decreasing the elapsed time to respond to an emergency is a goal of Emergency Medical Services (EMS). The size of the ambulance fleet and the location of ambulances within the service area are two factors that the EMS planners can control; these two factors directly affect the system's response time and contribute to the attainment of this goal. In this paper, a maximal expected coverage location model with time variation (TIMEXCLP) is developed and integrated into a decision support system to aid EMS planners to allocate vehicles within their service area. In applying TIMEXCLP to the Louisville, Kentucky, EMS system, response time was decreased by 36%.