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Cited 6 time in webofscience Cited 7 time in scopus
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A new self-adaptive algorithm for solving pseudomonotone variational inequality problems in Hilbert spaces

Authors
Duong Viet, ThongVan Long, LuongLi, Xiao-HuanDong, Qiao-LiCho, Yeol JeTuan, Pham Anh
Issue Date
Dec-2022
Publisher
Taylor & Francis
Keywords
Subgradient extragradient method; inertial method; variational inequality problem; pseudomonotone mapping; Lipschitz continuity; convergence rate
Citation
Optimization, v.71, no.12, pp 3669 - 3693
Pages
25
Indexed
SCIE
SCOPUS
Journal Title
Optimization
Volume
71
Number
12
Start Page
3669
End Page
3693
URI
https://scholarworks.gnu.ac.kr/handle/sw.gnu/71882
DOI
10.1080/02331934.2021.1909584
ISSN
0233-1934
1029-4945
Abstract
In this paper, we revisit the subgradient extragradient method for solving a pseudomonotone variational inequality problem with the Lipschitz condition in real Hilbert spaces. A new algorithm based on the subgradient extragradient method with the technique of choosing a new step size is proposed. The weak convergence of the proposed algorithm is established under the pseudomonotonicity and the Lipschitz continuity as well as without using the sequentially weakly continuity of the variational inequality mapping and the nonasymptotic O(1/n) convergence rate of the proposed algorithm is presented, while the strong convergence theorem of the proposed algorithm is also proved under the strong pseudomonotonicity and the Lipschitz continuity hypotheses. In order to show the computational effectiveness of our algorithm, some numerical results are provided.
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