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