AI-Driven Optimization for EDA: Balancing Symmetry and Asymmetry
A special issue of Symmetry (ISSN 2073-8994). This special issue belongs to the section "Computer".
Deadline for manuscript submissions: 31 May 2026 | Viewed by 156
Special Issue Editors
Interests: optimization; evolutionary algorithms; research methods; neural networks; low power application; cmos layout design; analog mixed-signal ic; biomedical applications; analog ic design; mos circuit design and layout
Special Issue Information
Dear Colleagues,
The growing complexity of Electronic Design Automation (EDA) calls for intelligent, adaptive solutions. As AI-driven optimization methods—such as machine learning, deep learning, and metaheuristics—become integral to EDA workflows, the roles of symmetry and asymmetry in circuit structures and design processes have become increasingly relevant. Symmetry often underpins balanced circuit topologies and regular layouts, contributing to improved performance and manufacturability. In contrast, asymmetry arises naturally due to design constraints, parasitics, mismatches, or performance trade-offs, and, when properly exploited, can offer optimization advantages.
This Special Issue aims to explore how understanding and leveraging symmetry and asymmetry can enhance AI-driven optimization techniques in EDA. We invite high-quality original research and review articles that address this interplay and contribute to smarter, more efficient electronic system design.
Topics of interest include (but are not limited to) the following:
- Symmetry-aware deep learning models for EDA;
- Asymmetry in optimization;
- Symmetric/asymmetric circuit sizing and placement;
- Optimization algorithms;
- Machine learning for parasitic-aware design;
- Design rule-aware layout generation using symmetry principles;
- Symmetry-breaking techniques in evolutionary optimization.
We welcome both theoretical insights and practical implementations that bridge AI, optimization, and EDA through the lens of symmetry and asymmetry.
Dr. Abdelaziz Lberni
Prof. Dr. Abdelaziz Ahaitouf
Guest Editors
Manuscript Submission Information
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Keywords
- AI-driven optimization
- electronic design automation
- symmetry in circuit design
- asymmetry in optimization
- machine learning in EDA
- neural networks and their applications in EDA
- metaheuristic algorithms
- deep learning for design automation
- design space exploration
- circuit optimization
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