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Cited 13 time in webofscience Cited 13 time in scopus
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Modified accelerated algorithms for solving variational inequalities

Authors
Dang Van HieuCho, Yeol JeXiao, Yi-bin
Issue Date
Nov-2020
Publisher
Taylor & Francis
Keywords
Variational inequality; monotone operator; extragradient method; subgradient extragradient method; projection method
Citation
International Journal of Computer Mathematics, v.97, no.11, pp 2233 - 2258
Pages
26
Indexed
SCIE
SCOPUS
Journal Title
International Journal of Computer Mathematics
Volume
97
Number
11
Start Page
2233
End Page
2258
URI
https://scholarworks.gnu.ac.kr/handle/sw.gnu/71896
DOI
10.1080/00207160.2019.1686487
ISSN
0020-7160
1029-0265
Abstract
In this paper, we propose two inertial algorithms with new stepsize rule for solving a monotone and Lipschitz variational inequality in a Hilbert space and prove some weak and strong convergence theorems of the proposed inertial algorithms. The algorithms use variable stepsizes which are updated at each iteration by a simple computation without any linesearch. A new stepsize rule presented in the paper has allowed the algorithms to work without the prior knowledge of Lipschitz constant of operator. Finally, we give several numerical results to demonstrate the computational performance of the new algorithms in comparison with other algorithms.
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