Kangtunyakarn, Atid

Loading...
Thumbnail Image
Preferred name
Kangtunyakarn, Atid
Alternative Name
Kangtunyakarn, A.
Main Affiliation
Email
atid.ka@kmitl.ac.th

Settings

Now showing 1 - 2 of 2
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
    Modified Halpern Iteration for Finding a Common Element of the Set of Solutions of Generalized Equilibrium Problem and Fixed Point Problem of Quasi-nonexpansive Mapping
    (2025-09-01)
    Sripattanet, Anchalee
    ;
    Kangtunyakarn, Atid
    In this paper, we introduce an iterative process for finding a common element of the set of solutions of generlized equilibrium problem and the set of fixed points problem of a quasi-nonexpansive mapping without demi-closed condition and T<inf>ω</inf>:= (1 − ω)I + ωT, where T is a quasi-nonexpansive mapping and ω ∈ (0,<sup>1</sup>) in a framework of a real Hilbert space. By using our main result, we obtain 2 strong convergence theorems involving finite families of nonspreading mapping and κ-demicontractive mapping.
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
    An Enhanced Subgradient Extragradient Method for Fixed Points of Quasi-Nonexpansive Mappings Without Demi-Closedness
    (2025-09-01)
    Sripattanet, Anchalee
    ;
    Kangtunyakarn, Atid
    This research focuses on developing a novel approach to finding fixed points of quasi-nonexpansive mappings without relying on the demi-closedness condition, a common requirement in previous studies. The approach is based on the Subgradient Extragradient technique, which builds upon the foundational extragradient method introduced by G.M. Korpelevich. Korpelevich’s method is a widely recognized tool in the fields of optimization and variational inequalities. This study extends Korpelevich’s technique by adapting it to a broader class of operators while maintaining critical convergence properties. This research demonstrates the effectiveness and practical applicability of this new method through detailed computational examples, highlighting its potential to address complex mathematical problems across various domains.