A self-adaptive inertial extragradient method for a class of split pseudomonotone variational inequality problems

被引:1
|
作者
Owolabi, Abd-Semii Oluwatosin-Enitan [1 ]
Alakoya, Timilehin Opeyemi [1 ]
Mewomo, Oluwatosin Temitope [1 ]
机构
[1] Univ KwaZulu Natal, Sch Math Stat & Comp Sci, Durban, South Africa
来源
OPEN MATHEMATICS | 2023年 / 21卷 / 01期
关键词
split pseudomonotone variational inequality problem; inertial technique; fixed point problem; non-Lipschitz operators; quasi-pseudocontractive mappings; VISCOSITY APPROXIMATION METHODS; FEASIBILITY PROBLEMS; STRONG-CONVERGENCE; GRADIENT METHODS;
D O I
10.1515/math-2022-0571
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
In this article, we study a class of pseudomonotone split variational inequality problems (VIPs) with non-Lipschitz operator. We propose a new inertial extragradient method with self-adaptive step sizes for finding the solution to the aforementioned problem in the framework of Hilbert spaces. Moreover, we prove a strong convergence result for the proposed algorithm without prior knowledge of the operator norm and under mild conditions on the control parameters. The main advantages of our algorithm are: the strong convergence result obtained without prior knowledge of the operator norm and without the Lipschitz continuity condition often assumed by authors; the minimized number of projections per iteration compared to related results in the literature; the inertial technique employed, which speeds up the rate of convergence; and unlike several of the existing results in the literature on VIPs with non-Lipschitz operators, our method does not require any linesearch technique for its implementation. Finally, we present several numerical examples to illustrate the usefulness and applicability of our algorithm.
引用
收藏
页数:28
相关论文
共 50 条
  • [1] Self-adaptive inertial subgradient extragradient scheme for pseudomonotone variational inequality problem
    Abubakar, Jamilu
    Kumam, Poom
    Rehman, Habib Ur
    INTERNATIONAL JOURNAL OF NONLINEAR SCIENCES AND NUMERICAL SIMULATION, 2022, 23 (01) : 77 - 96
  • [2] Self-adaptive subgradient extragradient method for solving pseudomonotone variational inequality problems in Banach spaces
    Xie, Zhongbing
    Cai, Gang
    Li, Xiaoxiao
    Dong, Qiao-Li
    BANACH JOURNAL OF MATHEMATICAL ANALYSIS, 2022, 16 (01)
  • [3] Self-adaptive subgradient extragradient method for solving pseudomonotone variational inequality problems in Banach spaces
    Zhongbing Xie
    Gang Cai
    Xiaoxiao Li
    Qiao-Li Dong
    Banach Journal of Mathematical Analysis, 2022, 16
  • [4] Self adaptive inertial extragradient algorithms for solving bilevel pseudomonotone variational inequality problems
    Bing Tan
    Liya Liu
    Xiaolong Qin
    Japan Journal of Industrial and Applied Mathematics, 2021, 38 : 519 - 543
  • [5] Self adaptive inertial subgradient extragradient algorithms for solving pseudomonotone variational inequality problems
    Duong Viet Thong
    Dang Van Hieu
    Themistocles M. Rassias
    Optimization Letters, 2020, 14 : 115 - 144
  • [6] Self adaptive inertial extragradient algorithms for solving bilevel pseudomonotone variational inequality problems
    Tan, Bing
    Liu, Liya
    Qin, Xiaolong
    JAPAN JOURNAL OF INDUSTRIAL AND APPLIED MATHEMATICS, 2021, 38 (02) : 519 - 543
  • [7] Self-adaptive inertial extragradient algorithms for solving variational inequality problems
    Tan, Bing
    Fan, Jingjing
    Li, Songxiao
    COMPUTATIONAL & APPLIED MATHEMATICS, 2021, 40 (01):
  • [8] Self-adaptive inertial extragradient algorithms for solving variational inequality problems
    Bing Tan
    Jingjing Fan
    Songxiao Li
    Computational and Applied Mathematics, 2021, 40
  • [9] Self adaptive inertial subgradient extragradient algorithms for solving pseudomonotone variational inequality problems
    Duong Viet Thong
    Dang Van Hieu
    Rassias, Themistocles M.
    OPTIMIZATION LETTERS, 2020, 14 (01) : 115 - 144
  • [10] Novel inertial extragradient method for solving pseudomonotone variational inequality problems
    Thong, Duong Viet
    Li, Xiao-Huan
    Dung, Vu Tien
    Huyen, Pham Thi Huong
    Tam, Hoang Thi Thanh
    OPTIMIZATION, 2024,