Analysis of two versions of relaxed inertial algorithms with Bregman divergences for solving variational inequalities
  • Jolaoso, Lateef Olakunle
  • Sunthrayuth, Pongsakorn
  • Cholamjiak, Prasit
  • Cho, Yeol Je
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초록

In this paper, we introduce and analyze two new inertial-like algorithms with the Bregman divergences for solving the pseudomonotone variational inequality problem in a real Hilbert space. The first algorithm is inspired by the Halpern-type iteration and the subgradient extragradient method and the second algorithm is inspired by the Halpern-type iteration and Tseng's extragradient method. Under suitable conditions, we prove some strong convergence theorems of the proposed algorithms without assuming the Lipschitz continuity and the sequential weak continuity of the given mapping. Finally, we give some numerical experiments with various types of Bregman divergence to illustrate the main results. In fact, the results presented in this paper improve and generalize the related works in the literature.

키워드

Bregman divergenceHilbert spaceStrong convergenceVariational inequality problemPseudomonotone mappingSTRONG-CONVERGENCEFIXED-POINTSEXTRAGRADIENT METHODNONEXPANSIVE-MAPPINGSMONOTONE-OPERATORSPROXIMAL METHODAPPROXIMATIONPROJECTIONWEAK
제목
Analysis of two versions of relaxed inertial algorithms with Bregman divergences for solving variational inequalities
저자
Jolaoso, Lateef OlakunleSunthrayuth, PongsakornCholamjiak, PrasitCho, Yeol Je
DOI
10.1007/s40314-022-02006-x
발행일
2022-10
유형
Article
저널명
Computational and Applied Mathematics
41
7