Dynamic model for real-time ambulance relocations based on coverage variation

Dynamic real-time relocation of ambulances throughout the day is one of the most important issues that emergency medical services have to consider. Ambulance relocation decisions must be made online under time constraints to guarantee timely response to future accidents as well as optimum regional coverage. We develop a two-stage optimization model to satisfy the objectives included in the problem. To find the optimum solution for our model, we use simulated annealing search along with various problem-specific heuristics. Our case study is based on real data from an emergency services provider in the city of Ottawa, corresponding to making online relocation decisions for emergency responders. We simulate sample days using a historical data set of accidents and apply our optimization models and heuristics during the simulation. We evaluate the performance of our model and solution methods using the simulation results.