A new trust region algorithm for nonsmooth convex minimization

摘要

It is well known that a possibly nonsmooth convex minimization problem can be transformed into a differentiable convex optimization problem by using the Moreau-Yosida regularization. This paper presents a new trust region method to solve the latter problem. Under some reasonable assumptions, the proposed algorithm is shown to be globally and Q-superlinearly convergent.