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Metaheuristics represent an important class of techniques to solve, approximately, hard combinatorial optimization problems for which the use of exact methods is impractical. In this work, one proposes a hybrid version of the GRASP metaheuristic, which incorporates a data mining process, to solve the p-median problem. The paper believes that patterns obtained by a data mining technique, from a set of sub-optimal solutions of a combinatorial optimization problem, can be used to guide metaheuristic procedures in the search for better solutions. Traditional GRASP is an iterative metaheuristic which returns the best solution reached over all iterations. In the hybrid GRASP proposal, after executing a significant number of iterations, the data mining process extracts pat-terns from an elite set of sub-optimal solutions for the p-median problem.
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