Abstract
This paper presents a competitive algorithm that combines the Greedy Randomized Adaptive Search Procedure including a Tabu Search instead of a traditional Local Search framework, with a Strategic Oscillation post-processing, to provide high-quality solutions for the -neighbor -center problem (CP). This problem seeks to locate facilities to service or cover a set of demand points with the objective of minimizing the maximum distance between each demand point and its -th nearest facility. The algorithm is compared to the best method found in the state of the art, which is an extremely efficient exact procedure for the continuous variant of the problem. An extensive comparison shows the relevance of the proposal, being able to provide competitive results independently of the value.
Jesús Sánchez-Oro
Associate Professor
Associate Professor at the Computer Science Department, being one of the senior researchers of the Group for Research on Algorithms For Optimization GRAFO.