Weak convergence of a relaxed and inertial hybrid projection-proximal point algorithm for maximal monotone operators in Hilbert space

Alvarez, F.

Abstract

This paper introduces a general implicit iterative method for finding zeros of a maximal monotone operator in a Hilbert space which unifies three previously studied strategies: relaxation, inertial type extrapolation and projection step. The first two strategies are intended to speed up the convergence of the standard proximal point algorithm, while the third permits one to perform inexact proximal iterations with fixed relative error tolerance. The paper establishes the global convergence of the method for the weak topology under appropriate assumptions on the algorithm parameters.

Más información

Título según WOS: Weak convergence of a relaxed and inertial hybrid projection-proximal point algorithm for maximal monotone operators in Hilbert space
Título según SCOPUS: Weak convergence of a relaxed and inertial hybrid projection-proximal point algorithm for maximal monotone operators in Hilbert space
Título de la Revista: SIAM JOURNAL ON OPTIMIZATION
Volumen: 14
Número: 3
Editorial: SIAM PUBLICATIONS
Fecha de publicación: 2004
Página de inicio: 773
Página final: 782
Idioma: English
DOI:

10.1137/S1052623403427859

Notas: ISI, SCOPUS