Krasnosel’skiǐ–Mann-Type Subgradient Extragradient Algorithms for Variational Inequality and Hierarchical Fixed-Point Problems

In this work, we present a Krasnosel’skiǐ–Mann-type subgradient extragradient algorithm to solve variational inequalities and hierarchical fixed-point problems for nonexpansive and quasi-nonexpansive mappings in Hilbert spaces. We establish weak convergence of the generated sequences to a common solution and derive several related results. The algorithm is validated through numerical examples, and several applications are discussed to demonstrate the method’s applicability. The proposed approach extends and unifies existing methods and findings in this field.

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Publication Details

Journal
Mathematics
Published
2025-11-21
DOI
https://doi.org/10.3390/math13233740
Primary Topic
Optimization and Variational Analysis
Type
article
Field-Weighted Citation Impact
0.00

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article

Krasnosel’skiǐ–Mann-Type Subgradient Extragradient Algorithms for Variational Inequality and Hierarchical Fixed-Point Problems

Monairah Alansari, Rehan Ali, Mohammad Farid
Mathematics
Optimization and Variational Analysis
article

Krasnosel’skiǐ–Mann-Type Subgradient Extragradient Algorithms for Variational Inequality and Hierarchical Fixed-Point Problems

Monairah Alansari, Rehan Ali, Mohammad Farid
article en

Abstract

In this work, we present a Krasnosel’skiǐ–Mann-type subgradient extragradient algorithm to solve variational inequalities and hierarchical fixed-point problems for nonexpansive and quasi-nonexpansive mappings in Hilbert spaces. We establish weak convergence of the generated sequences to a common solution and derive several related results. The algorithm is validated through numerical examples, and several applications are discussed to demonstrate the method’s applicability. The proposed approach extends and unifies existing methods and findings in this field.

MathematicsVol. 13(23)
Qassim University (SA), King Abdulaziz University (SA), Central University of Kashmir (IN)
Qassim University
Openalex Percentile: Top 64%
Optimization and Variational Analysis
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