Weak and strong convergence of a modified double inertial projection algorithm for solving variational inequality problems

被引：2
|
作者：
Zhang, Huan [1 ]
Liu, Xiaolan [1 ,2 ,3 ]
机构：
[1] Sichuan Univ Sci & Engn, Coll Math & Stat, Zigong 643000, Sichuan, Peoples R China
[2] South Sichuan Ctr Appl Math, Zigong 643000, Sichuan, Peoples R China
[3] Artificial Intelligence Key Lab Sichuan Prov, Zigong 643000, Sichuan, Peoples R China
来源：
COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION | 2024年 / 130卷
基金：
中国国家自然科学基金;
关键词：
Double inertial; Variational inequality; Weak convergence; Strong convergence; SUBGRADIENT EXTRAGRADIENT METHOD;
D O I：
10.1016/j.cnsns.2023.107766
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
We propose a new double inertial projection algorithm by combining the subgradient extra gradient algorithm with the projection contraction algorithm. On one hand, our algorithm requires the mapping to be Lipschitz continuous, but without the Lipschitz constant. On the other hand, this algorithm only requires the mapping is quasimonotone.Under some mild conditions, we obtain a weak convergence result of the algorithm. In addition, we give a strong convergence result of the algorithm when the mapping is strongly pseudomonotone. Some numerical experiments are given to show the effectiveness of the proposed algorithm.
引用
收藏
页数：15
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