Symmetry and Asymmetry in Computer Algorithms: Properties and Applications

Dear Colleagues,

Symmetry and asymmetry are key concepts in the formulation, optimization, and practical deployment of modern computer algorithms. Symmetry can simplify computation, enable invariance-based reasoning, and improve efficiency by exploiting structural regularities in data, models, or problem domains. Conversely, asymmetry introduces diversity, specialization, and adaptability—characteristics often required to address realistic settings where information, constraints, and environments are heterogeneous and dynamic. This Special Issue seeks contributions that explore both theoretical and practical perspectives on the use of symmetry and asymmetry in algorithmic research. In addition to fundamental studies, we particularly welcome works that demonstrate the practical impact of these concepts in solving real-world problems. Applications may span energy systems, healthcare, transportation, education, smart cities, robotics, cybersecurity, and large-scale data analysis. We are especially interested in contributions in machine learning and data mining that show how symmetry-aware or asymmetry-driven models and algorithms improve performance, scalability, interpretability, or robustness in the presence of complex and high-dimensional data. By integrating theoretical advances with concrete applications, this Special Issue aims to highlight how the interplay of symmetry and asymmetry can drive innovation not only at the conceptual and mathematical levels but also in high-impact domains where algorithms contribute directly to scientific, industrial, and societal progress.

We invite you to submit original research and review articles focused on the role of symmetry and asymmetry in modern computer algorithms. Symmetry and asymmetry provide complementary lenses for understanding, designing, and deploying algorithms that are both mathematically principled and effective in realistic, heterogeneous environments. By bringing together contributions from theory, methodology, and applications, this Special Issue aims to foster cross-disciplinary dialogue among researchers working in algorithms, optimization, machine learning, data mining, and domain-specific computational sciences.

This Special Issue also aims to explore how symmetry and asymmetry can be systematically exploited to formulate, analyze, and implement advanced algorithmic solutions, in line with the journal’s focus on algorithms, computational methods, and their applications. On the one hand, symmetry can reduce problem complexity, support invariance-based reasoning, and improve computational efficiency by leveraging regularities in data, models, or problem structures. On the other hand, asymmetry enables specialization, diversity, and adaptability, which are essential in heterogeneous and dynamic environments. We particularly welcome contributions that connect rigorous theoretical developments with concrete, real-world use cases in which symmetry-aware or asymmetry-driven algorithms provide measurable benefits in terms of performance, scalability, interpretability, or robustness. The scope is provided in the journal menu under “Aims & Scope” and should not be too broad or narrow.

Suggested themes and article types for submissions

This Special Issue welcomes original research articles and reviews focused on but not limited to the following topics:

• Theoretical foundations of symmetry and asymmetry in algorithms and optimization;
• Symmetry groups, invariances, and equivariance in algorithm design and analysis;
• Asymmetry in models, architectures, and resource allocation for large-scale computing;
• Symmetry-aware and asymmetry-driven methods in machine learning and data mining;
• Algorithms for complex, high-dimensional, and heterogeneous data;
• Applications in energy systems, smart grids, and sustainable infrastructure;
• Applications in healthcare, personalized medicine, and biomedical data analysis;
• Applications in transportation, logistics, and mobility systems;
• Applications in smart cities, robotics, and autonomous systems;
• Applications in cybersecurity, anomaly detection, and threat

We look forward to receiving your contributions.

Dr. Yoan Martínez López
Dr. Ansel Yoan Rodríguez González
Dr. Julio Madera Quintana
Guest Editors

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 250 words) can be sent to the Editorial Office for assessment.

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.

• symmetry and asymmetry
• algorithm design
• applied optimization
• evolutionary computation
• machine learning and artificial intelligence
• data mining, real-world problem solving
• large-scale data analysis
• smart systems and applications
• bioinspired and nature-based algorithms