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General Information
    • ISSN: 2010-3697
    • Frequency: Bimonthly
    • DOI: 10.7763/IJMO
    • Editor-in-Chief: Prof. Adrian Olaru
    • Executive Editor: Ms.Yoyo Y. Zhou
    • Abstracting/ Indexing: Engineering & Technology Digital Library, ProQuest, Crossref, Electronic Journals Library, Google Scholar, EI (INSPEC, IET).
    • E-mail ijmo@iacsitp.com
Editor-in-chief
Prof. Adrian Olaru
University Politehnica of Bucharest, Romania
I'm happy to take on the position of editor in chief of IJMO. It's a journal that shows promise of becoming a recognized journal in the area of modelling and optimization. I'll work together with the editors to help it progress.
IJMO 2015 Vol.5(2): 150-154 ISSN: 2010-3697
DOI: 10.7763/IJMO.2015.V5.452

Enhanced Genetic Algorithm with K-Means for the Clustering Problem

N. Bouhmala, A. Viken, and J. B. Lønnum
Abstract—In this paper, an algorithm for the clustering problem using a combination of the genetic algorithm with the popular K-Means greedy algorithm is proposed. The main idea of this algorithm is to use the genetic search approach to generate new clusters using the famous two-point crossover and then apply the K-Means technique to further improve the quality of the formed clusters in order to speed up the search process. Experimental results demonstrate that the proposed genetic algorithm combined with K-Means converges faster while producing the same quality of the clustering compared to the standard genetic algorithm.

Index Terms—Clustering problem, genetic algorithm, K-means.

The authors are with Buskerud and Vestfold University College, Faculty of Technology, Norway (e-mail: noureddine.bouhmala@hbv.no).

[PDF]

Cite: N. Bouhmala, A. Viken, and J. B. Lønnum, "Enhanced Genetic Algorithm with K-Means for the Clustering Problem," International Journal of Modeling and Optimization vol. 5, no. 2, pp. 150-154, 2015.

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