HYBRID PROXIMAL POINT ALGORITHMS FOR SOLVING CONSTRAINED MINIMIZATION PROBLEMS IN BANACH SPACES

Abstract

The purpose of this paper is to introduce two hybrid proximal point algorithms to solve the constrained minimization problem for a convex functional in a uniformly convex and uniformly smooth Banach space. Using those iterative schemes, we establish the strong convergence theorems for relatively nonexpansive mappings which generalize the recent results in the literature.