Strong convergence theorems for solving pseudo-monotone variational inequality problems and applications

In this paper, we introduce two different kinds of iterative algorithms, which are based on the inertial Tseng's method and the viscosity method. They are intended to solve the variational inequality problems governed by the mappings of pseudo-monotone type. Strong convergence theorems are esta...

Full description

Saved in:
Bibliographic Details
Published inOptimization Vol. 71; no. 12; pp. 3603 - 3626
Main Authors Liu, Liya, Qin, Xiaolong
Format Journal Article
LanguageEnglish
Published Philadelphia Taylor & Francis 02.12.2022
Taylor & Francis LLC
Subjects
Convergence
Fuzzy logic
fuzzy programming model
Fuzzy sets
Hilbert space
inertial extrapolation
Iterative algorithms
pseudomonotonicity
Theorems
Tseng's method
Variational inequality
Online AccessGet full text

Cover

More Information
Summary:In this paper, we introduce two different kinds of iterative algorithms, which are based on the inertial Tseng's method and the viscosity method. They are intended to solve the variational inequality problems governed by the mappings of pseudo-monotone type. Strong convergence theorems are established in Hilbert spaces. Practical examples in fuzzy environment are given to show the applicability and effectiveness of the proposed algorithms.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:0233-1934
1029-4945
DOI:10.1080/02331934.2021.1905641