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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 combineddoi:10.7763/ijmo.2015.v5.452 fatcat:erunsdm4bjgxxezeyu24goahda