Symmetry and Asymmetry in Optimization Algorithms and Control Systems

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

Deadline for manuscript submissions: closed (26 January 2026) | Viewed by 1004

Special Issue Editors


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Guest Editor
Intelligent Transportation Systems Research Center, Wuhan University of Technology, 430063, Hubei, China
Interests: optimization management and control of water transportation systems; dynamic modeling, path planning, control, and application of USV
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Guest Editor
School of Computer Science and Engineering, Tianjin University of Technology, Tianjin 300381, China
Interests: digital twin of ships; big data processing and optimization application
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
College of Mathematics and Computer Science, Wuhan Polytechnic University, Wuhan, China
Interests: coordination and optimization control of water transportation systems; navigation and control of USV

Special Issue Information

Dear Colleagues,

This Special Issue, titled “Symmetry and Asymmetry in Optimization Algorithms and Control Systems”, examines the profound role that symmetric and asymmetric structures play in the development and performance of optimization algorithms and control systems. Symmetry often simplifies mathematical models, leading to more efficient algorithms with reduced computational costs. However, asymmetry is equally important in addressing the complexities of real-world systems, particularly those that are nonlinear, dynamic, or uncertain.

This Special Issue explores the delicate balance between utilizing symmetry for computational efficiency and incorporating asymmetry to enhance system robustness and adaptability. The topics covered in this Special Issue include the following: symmetry-based optimization techniques, the impact of asymmetry on system dynamics, and the design of novel algorithms that effectively handle both symmetric and asymmetric challenges. The goal of this Special Issue is to advance our understanding of how these concepts influence the stability, scalability, and performance of both optimization methods and control strategies, with applications ranging from theoretical modeling to practical implementation in diverse fields.

Dr. Man Zhu
Dr. Xu Cheng
Dr. Wei Tao
Guest Editors

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Keywords

  • symmetry in optimization
  • asymmetry in systems control
  • computational complexity reduction
  • robust control design
  • nonlinear optimization
  • adaptive control systems
  • symmetry breaking
  • stability analysis in asymmetric systems
  • mathematical modeling of symmetry and asymmetry
  • scalability of optimization algorithms

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Published Papers (1 paper)

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Research

17 pages, 2662 KB  
Article
A Swin-Transformer-Based Network for Adaptive Backlight Optimization
by Jin Li, Rui Pu, Junbang Jiang and Man Zhu
Symmetry 2026, 18(3), 502; https://doi.org/10.3390/sym18030502 - 15 Mar 2026
Cited by 1 | Viewed by 365
Abstract
Mini-LED local dimming systems commonly suffer from luminance discontinuity, halo artifacts, and temporal instability in dynamic scenes. Traditional heuristic-based methods and standard convolutional neural networks often fail to capture long-range spatial dependencies and struggle to balance spatial smoothness, content fidelity, and real-time performance [...] Read more.
Mini-LED local dimming systems commonly suffer from luminance discontinuity, halo artifacts, and temporal instability in dynamic scenes. Traditional heuristic-based methods and standard convolutional neural networks often fail to capture long-range spatial dependencies and struggle to balance spatial smoothness, content fidelity, and real-time performance under hardware constraints. To address these challenges, this paper proposes SwinLightNet, an efficient adaptive backlight optimization network tailored for Mini-LED displays. Built upon a Swin Transformer framework tailored for Mini-LED backlight optimization, SwinLightNet integrates five hardware-aware design strategies: (i) a lightweight Swin variant (window size = 8, MLP ratio = 2.0) for efficient global context modeling; (ii) CNN encoder–decoder integration for multi-scale feature extraction; (iii) a partition-level alignment module ensuring spatial consistency; (iv) a backlight constraint module enforcing local luminance consistency and contrast preservation; (v) a change-aware temporal decision framework stabilizing dynamic sequences. These components synergistically resolve core limitations: global modeling suppresses halo artifacts while preserving content fidelity; alignment and constraint modules eliminate luminance discontinuity without compromising contrast; and the temporal framework guarantees flicker-free output under motion. Evaluated on DIV2K (static images) and a custom 2K-resolution video dataset (dynamic scenes), SwinLightNet demonstrates robust reconstruction quality while maintaining only 1.18 million parameters and 0.088 GFLOPs (Computational Cost). The results confirm SwinLightNet’s effectiveness in holistically addressing spatial, temporal, and hardware constraints, demonstrating strong potential for practical deployment in resource-constrained Mini-LED backlight control systems. Full article
(This article belongs to the Special Issue Symmetry and Asymmetry in Optimization Algorithms and Control Systems)
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