A hybrid data mining metaheuristic for the p-median problem

Plastino, Alexandre and Fuchshuber, Richard and Martins, Simone de L. and Freitas, Alex A. and Salhi, Said (2011) A hybrid data mining metaheuristic for the p-median problem. Statistical Analysis & Data Mining Journal , 4 (3). pp. 313-335. (The full text of this publication is not available from this repository)

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Official URL
http://dx.doi.org/10.1002/sam.10116

Abstract

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 Greedy Randomized Adaptive Search Procedures (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 suboptimal 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 suboptimal solutions for the p-median problem. These patterns present characteristics of near optimal solutions and can be used to guide the following GRASP iterations in the search through the combinatorial solution space. Computational experiments, comparing traditional GRASP and different data mining hybrid proposals for the p-median problem, showed that employing patterns mined from an elite set of suboptimal solutions made the hybrid GRASP find better results. Besides, the conducted experiments also evidenced that incorporating a data mining technique into a metaheuristic accelerated the process of finding near optimal and optimal solutions. © 2011 Wiley Periodicals, Inc. Statistical Analysis and Data Mining 2011

Item Type: Article
Uncontrolled keywords: hybrid metaheuristics; GRASP; data mining; p-median problem; combinatorial optimization
Subjects: H Social Sciences > H Social Sciences (General)
Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming,
Divisions: Faculties > Science Technology and Medical Studies > School of Computing
Faculties > Science Technology and Medical Studies > School of Computing > Computational Intelligence Group
Faculties > Social Sciences > Kent Business School > Management Science
Depositing User: Kasia Senyszyn
Date Deposited: 14 Oct 2011 09:19
Last Modified: 19 May 2014 15:52
Resource URI: http://kar.kent.ac.uk/id/eprint/28231 (The current URI for this page, for reference purposes)
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