A Hybrid Data Mining Metaheuristic for the p-Median Problem.

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, we propose a hybrid version of the GRASP metaheuristic, which incorporates a data mining process, to solve the p-median problem. We believe 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 patterns from an elite set of sub-optimal solutions for the pmedian problem. These patterns present characteristics of near optimal solutions and can be used to guide the following GRASP iterations in the search through the combinatori...

• Type: Conference
• Year: 2009
• Where: SDM
• Authors: Alexandre Plastino, Erick R. Fonseca, Richard Fuchshuber, Simone L. Martins, Alex Alves Freitas, Martino Luis, Saïd Salhi
• Keywords: Computer Science, Data Mining Hybrid, Hybrid Grasp Proposal, SDM 2009, Traditional Grasp