Solving two location models with few facilities by using a hybrid heuristic: a real health resources case

We propose a metaheuristic procedure based on the scatter search approach for solving two location problems with few facilities (p 10). The first problem is the well-known p-center problem. The second one is the maximum set covering problem (MSCP). This scatter search algorithm incorporates procedures based on different strategies, such as local search, GRASP, and path relinking. We first designed the algorithm for the p-center problem, and then modified it for the MSCP. The aim is to solve problems with real data provided by the Health Authorities of Burgos (northern Spain). Because the authorities have a limited budget, less than 10 facilities can considered in both problems. A series of computational experiments were also performed. The proposed algorithm gave similar results to the recently reported methods for the p-center problem but much faster. The quality of the solutions is also very good for the MSCP (less than 1% deviation from the lower bound). We show its application to the location of health resources with real data in the province of Burgos.