Symmetry in Fixed Point Theory and Optimization: Computations and Applications

A special issue of Symmetry (ISSN 2073-8994). This special issue belongs to the section "Mathematics".

Deadline for manuscript submissions: 20 March 2026 | Viewed by 3562

Special Issue Editor


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Guest Editor
1. Department of Mathematics, Faculty of Science, Naresuan University, Phitsanulok 65000, Thailand
2. Center of Excellence in Nonlinear Analysis and Optimization, Faculty of Science, Naresuan University, Phitsanulok 65000, Thailand
Interests: optimization algorithms and its applications
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Special Issue Information

Dear Colleagues,

Symmetry is a foundational concept that resonates through diverse areas of mathematics and computer science, providing deep insights into the structures and dynamics of many analytical and computational processes. In fixed point theory and optimization, including vector optimization, linear programming, variational inequalities, and equilibrium problems, symmetrical principles often guide iterative schemes, enhance convergence properties, and inspire new approaches to challenging questions in mathematics, engineering, and computational applications.

This Special Issue, titled “Symmetry in Fixed Point Theory and Optimization: Computations and Applications”, will highlight both theoretical breakthroughs and practical advances that capitalize on symmetrical frameworks. We welcome submissions that address, but are not limited to, the following:

  1. Symmetry in Fixed Point Theory
    • Novel fixed point theorems exploiting symmetrical properties in various abstract spaces (metric, Banach, etc.);
    • Convergence analyses of iterative schemes under symmetrical constraints;
    • Fractional calculus approaches to fixed point problems.
  2. Symmetry in Optimization
    • Symmetrical structures and formulations in constrained/unconstrained optimization, including vector optimization and linear programming;
    • Variational inequalities and equilibrium problems that exploit symmetrical properties in their solution methodologies;
    • Approximation algorithms and stochastic systems demonstrating symmetrical advantages.
  3. Computational Approaches
    • Numerical methods, simulations, and software frameworks that utilize symmetry for improved convergence, reduced complexity, or more robust performance;
    • Cross-disciplinary collaborations linking mathematics and computer science to develop or apply symmetrical techniques for computational challenges.
  4. Applications
    • Symmetry-driven solutions in fields such as engineering, physics, finance, and machine learning;
    • Case studies on how symmetry provides deeper insights, reduces computational overheads, or fosters innovative methodological developments;
    • Broader impacts of symmetrical frameworks on modern computational science, algorithmic design, and data analysis.

We request original research articles, review articles, and short communications examining the influence and role of symmetry within the realms of fixed point theory, optimization, and computer science. By uniting experts across these domains, we will show how symmetrical considerations not only deepen theoretical understanding but also spark new applications and innovations.

We look forward to receiving valuable contributions that advance our understanding and utilization of symmetrical properties in fixed point theory and optimization.

Dr. Narin Petrot
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Symmetry is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • fixed point theory
  • nonlinear analysis
  • optimization (vector optimization, linear programming)
  • equilibrium and variational inequality problems
  • iterative algorithms
  • fractional calculus
  • stochastic systems
  • approximation algorithms
  • computer science

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Published Papers (2 papers)

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Research

36 pages, 544 KiB  
Article
Well-Posedness of Cauchy-Type Problems for Nonlinear Implicit Hilfer Fractional Differential Equations with General Order in Weighted Spaces
by Jakgrit Sompong, Samten Choden, Ekkarath Thailert and Sotiris K. Ntouyas
Symmetry 2025, 17(7), 986; https://doi.org/10.3390/sym17070986 - 22 Jun 2025
Viewed by 102
Abstract
This paper establishes the well-posedness of Cauchy-type problems with non-symmetric initial conditions for nonlinear implicit Hilfer fractional differential equations of general fractional orders in weighted function spaces. Using fixed-point techniques, we first prove the existence of solutions via Schaefer’s fixed-point theorem. The uniqueness [...] Read more.
This paper establishes the well-posedness of Cauchy-type problems with non-symmetric initial conditions for nonlinear implicit Hilfer fractional differential equations of general fractional orders in weighted function spaces. Using fixed-point techniques, we first prove the existence of solutions via Schaefer’s fixed-point theorem. The uniqueness and Ulam–Hyers stability are then derived using Banach’s contraction principle. By introducing a novel singular-kernel Gronwall inequality, we extend the analysis to Ulam–Hyers–Rassias stability and continuous dependence on initial data. The theoretical framework is unified for general fractional orders and validated through examples, demonstrating its applicability to implicit systems with memory effects. Key contributions include weighted-space analysis and stability criteria for this class of equations. Full article
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17 pages, 285 KiB  
Article
Convergence Analysis of Reinforcement Learning Algorithms Using Generalized Weak Contraction Mappings
by Abdelkader Belhenniche, Roman Chertovskih and Rui Gonçalves
Symmetry 2025, 17(5), 750; https://doi.org/10.3390/sym17050750 - 13 May 2025
Viewed by 562
Abstract
We investigate the convergence properties of policy iteration and value iteration algorithms in reinforcement learning by leveraging fixed-point theory, with a focus on mappings that exhibit weak contractive behavior. Unlike traditional studies that rely on strong contraction properties, such as those defined by [...] Read more.
We investigate the convergence properties of policy iteration and value iteration algorithms in reinforcement learning by leveraging fixed-point theory, with a focus on mappings that exhibit weak contractive behavior. Unlike traditional studies that rely on strong contraction properties, such as those defined by the Banach contraction principle, we consider a more general class of mappings that includes weak contractions. Employing Zamfirscu’s fixed-point theorem, we establish sufficient conditions for norm convergence in infinite-dimensional policy spaces under broad assumptions. Our approach extends the applicability of these algorithms to feedback control problems in reinforcement learning, where standard contraction conditions may not hold. Through illustrative examples, we demonstrate that this framework encompasses a wider range of operators, offering new insights into the robustness and flexibility of iterative methods in dynamic programming. Full article
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