Dual convergence for penalty proximal point algorithms in convex programming

Abstract

We consider an implicit iterative method in convex programming which combines inexact variants of the proximal point algorithm, with parametric penalty functions. We investigate a multiplier sequence which is explicitly computed in terms of the primal sequence generated by the iterative method, providing some conditions on the parameters in order to ensure convergence towards a particular dual optimal solution.