Heuristic Solution of an Extended Double-Coverage Ambulance Location Problem for Austria

In this paper, we present solution procedures to tackle an ambulance location problem in Austria. We consider the problem as a doublecoverage ambulance location problem, and for specifying it in formal terms, we use an extension of a model developed by Gendreau, Laporte and Semet [11] by introducing a limit on the number of inhabitants served per ambulance. To solve the problem, we reimplemented the Tabu Search algorithm 2 Karl F. Doerner et al. of [11] and developed an Ant Colony Optimization algorithm. Our computational tests are based on real location sites, the population census data and the real road network data of eight provinces of Austria. For the two smallest instances exact solutions can be found and used as a measure for the performance of the two metaheuristic algorithms. For these problem instances, both metaheuristics find the optimal solution easily. For the larger instances, Tabu Search and Ant Colony Optimization yield results of comparable quality. However, Tabu Search turns out as distinctively faster.