Hierarchical clustering based on mathematical optimization

In this paper a novel optimization model for bilevel hierarchical clustering has been proposed. This is a hard nonconvex, nons-mooth optimization problem for which we investigate an efficient technique based on DC (Difference of Convex functions) programming and DCA (DC optimization Algorithm). Preliminary numerical results on some artificial and real-world databases show the efficiency and the superiority of this approach with respect to related existing methods.