Solving the Euclidean k-median problem by DCA

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.