Matheuristics for the capacitated p-median problem

The recent evolution of computers and mathematical programming techniques has provide the development of a new class of algorithms called matheuristics. Associated with an improvement of MIP solvers, many of these methods have been successful applied to solve combinatorial problems. This work presents an approach that hybridizes metaheuristics based on local search and exact algorithms to solve the classic capacitated p-median problem. The proposal considers a reduced mathematical model performed by a heuristic elimination of variables which are less likely to belong to a good or optimal solution. In addition, an iterative local optimization algorithm based on reduction is proposed. In both cases, the mathematical model is solved by a MIP solver. Computational experiments involving three set of instances are presented to demonstrate the good performance of the developed approaches.