RT Journal Article
T1 A new grouping genetic algorithm for clustering problems
A1 Agustín-Blas, L. E.
A1 Salcedo-Sanz, S.
A1 Jiménez-Fernández, S.
A1 Carro-Calvo, L.
A1 Del Ser, J.
A1 Portilla-Figueras, J. A.
AB In this paper we present a novel grouping genetic algorithm for clustering problems. Though there have been different approaches that have analyzed the performance of several genetic and evolutionary algorithms in clustering, the grouping-based approach has not been, to our knowledge, tested in this problem yet. In this paper we fully describe the grouping genetic algorithm for clustering, starting with the proposed encoding, different modifications of crossover and mutation operators, and also the description of a local search and an island model included in the algorithm, to improve the algorithm's performance in the problem. We test the proposed grouping genetic algorithm in several experiments in synthetic and real data from public repositories, and compare its results with that of classical clustering approaches, such as K-means and DBSCAN algorithms, obtaining excellent results that confirm the goodness of the proposed grouping-based methodology.
SN 0957-4174
YR 2012
FD 2012-08
LA eng
NO Agustín-Blas , L E , Salcedo-Sanz , S , Jiménez-Fernández , S , Carro-Calvo , L , Del Ser , J & Portilla-Figueras , J A 2012 , ' A new grouping genetic algorithm for clustering problems ' , Expert Systems with Applications , vol. 39 , no. 10 , pp. 9695-9703 . https://doi.org/10.1016/j.eswa.2012.02.149
NO This work has been partially supported by Spanish Ministry of Science and Innovation, under a project number ECO2010-22065-C03-02.
DS TECNALIA Publications
RD 29 sept 2024