Solving the Euclidean k-median problem by DCA

Authors:
Le Thi Hoai An;Pham Dinh Tao
Affiliations:
Laboratory of Theoretical and Applied Computer Science, Paul Verlaine-Metz University, Metz, France;Laboratory of Modelling, Optimization and Operations Research, National Institute for Applied Sciences, Rouen, Saint-Etienne-du-Rouvray, France
Venue:
ACS'10 Proceedings of the 10th WSEAS international conference on Applied computer science
Year:
2010

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Abstract

In this paper, a novel optimization model for k-median clustering has been proposed. This is a hard nonconvex, nonsmooth optimization problem for which we investigate an efficient technique based on DC (Difference of Convex functions) programming and DCA (DC Algorithm). Preliminary numerical results on some real-world databases show the efficiency of the proposed approach.