Journal
APPLICABLE ANALYSIS
Volume 100, Issue 1, Pages 135-144Publisher
TAYLOR & FRANCIS LTD
DOI: 10.1080/00036811.2019.1594202
Keywords
Dumitru Motreanu; Subgradient extragradient algorithm; strong convergence; Lipschitz continuity; variational inequality; projection
Categories
Funding
- H2020-MSCA-RISE-2018 Research and Innovation Staff Exchange Scheme Fellowship [823731 CONMECH]
- National Science Center of Poland [UMO-2012/06/A/ST1/00262, 2017/25/N/ST1/00611]
- Ministry of Science and Higher Education of Republic of Poland [3792/GGPJ/H2020/2017/0]
- National Natural Science Foundation of China [11561007, 11561008, 11771350]
- Natural Sciences Foundation of Guangxi [2018JJA110006]
- Beibu Gulf University [2018KYQD06]
- Basic and Advanced Research Project of CQ CSTC [cstc2016jcyjA0163, cstc2018jcyjAX0605]
Ask authors/readers for more resources
This paper introduces a new algorithm for solving variational inequalities in Hilbert spaces, proving the strong convergence of the algorithm without the need for the Lipschitz constant of the operator. Additionally, several numerical experiments for the proposed algorithm are presented.
The goal of the note is to introduce a new modified subgradient extragradient algorithm for solving variational inequalities in Hilbert spaces. A result on the strong convergence of the algorithm is proved without the knowledge of Lipschitz constant of the operator. Several numerical experiments for the proposed algorithm are presented.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available
Share Paper
