Algorithms and Inertial Algorithms for Inverse Mixed Variational Inequality Problems in Hilbert Spaces

The inverse mixed variational inequality problem comes from classical variational inequality, and it has many applications. In this paper, we propose new algorithms to study the inverse mixed variational inequality problems in Hilbert spaces, and these algorithms are based on the generalized project...

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Bibliographic Details
Published inMathematics (Basel) Vol. 13; no. 12; p. 1966
Main Author Chuang, Chih-Sheng
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 01.06.2025
Subjects
Algorithms
Codes
Convergence
generalized projection
Hilbert space
Inequalities (Mathematics)
inertial algorithm
inverse strong monotonicity
inverse variational inequality
Theorems
variational inequality
Taiwan
Online AccessGet full text
ISSN2227-7390
2227-7390
DOI10.3390/math13121966

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Summary:The inverse mixed variational inequality problem comes from classical variational inequality, and it has many applications. In this paper, we propose new algorithms to study the inverse mixed variational inequality problems in Hilbert spaces, and these algorithms are based on the generalized projection operator. Next, we establish convergence theorems under inverse strong monotonicity conditions. In addition, we also provide inertial-type algorithms for the inverse mixed variational inequality problems with conditions that differ from the above convergence theorems.
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ISSN:2227-7390
2227-7390
DOI:10.3390/math13121966