Speech and Vision Lab

http://www.sciencedirect.com/science/article/B6V15-3SNYSW3-K/2/16b1cae05c201e40b7a8b1e7359d4fb8

In this paper, an evolutionary programming-based clustering algorithm is proposed. The algorithm effectively groups a given set of data into an optimum number of clusters. The proposed method is applicable for clustering tasks where clusters are crisp and spherical. This algorithm determines the number of clusters and the cluster centers in such a way that locally optimal solutions are avoided. The result of the algorithm does not depend critically on the choice of the initial cluster centers.