A bundle type approach to the unconstrained minimization of convex nonsmooth functions

A numerical method for the unconstrained minimization of a convex nonsmooth function of several variables is presented. It is closely related to the bundle type approach and to the conjugate subgradient method. A way is suggested to reduce the amount of information to be stored during the computational procedure. Global convergence of the method to the minimum is proved.