Title
LINEAR AND SUPERLINEAR CONVERGENCE OF AN INEXACT ALGORITHM WITH PROXIMAL DISTANCES FOR VARIATIONAL INEQUALITY PROBLEMS
Date Issued
01 February 2022
Access level
metadata only access
Resource Type
research article
Publisher(s)
House of the Book of Science
Abstract
This paper introduces an inexact proximal point algorithm using proximal distances with linear and superlinear rate of convergence for solving variational inequality problems when the mapping is pseudomonotone or quasimonotone. This algorithm is new even for the monotone case and from the theoretical point of view the error criteria used improves recent works in the literature.
Start page
311
End page
330
Volume
23
Issue
1
Language
English
OCDE Knowledge area
Ciencias de la computación
Scopus EID
2-s2.0-85123074740
Source
Fixed Point Theory
ISSN of the container
15835022
Sources of information: Directorio de Producción Científica Scopus