Swarm Intelligence and Optimization: Algorithms, Innovations, and Real-World Applications
A Special Issue of Mathematics (ISSN 2227-7390) belonging to the section "E: Applied Mathematics".
Deadline for manuscript submissions: 30 June 2027 | Viewed by 70
Editor
Special Issue Information
Dear Colleagues,
Swarm intelligence has emerged as a fast‑growing branch of computational intelligence, which inspires optimization algorithms from the collective behaviors of natural swarms, such as birds flocking, ant foraging and fish schooling. Owing to their strong global search capability, flexibility and robustness, swarm‑intelligence‑based optimization algorithms have attracted extensive attention across both academic research and industrial practice. These metaheuristic approaches are widely applied to tackle complex, non‑linear, non‑convex, high‑dimensional optimization problems that are difficult for traditional gradient‑based optimization methods.
This Special Issue, Swarm Intelligence and Optimization: Algorithms, Innovations, and Real-World Applications, aims to present high‑quality original research articles and comprehensive review papers focusing on recent theoretical advances, algorithmic innovations and practical implementations of swarm intelligence and related optimization techniques. We welcome contributions that report new swarm‑intelligence algorithm designs, theoretical convergence analysis, hybrid optimization frameworks, and real‑world case studies in engineering, data science, machine learning, sparse reconstruction and other related fields.
Potential topics include, but are not limited to, the following:
- Novel swarm intelligence optimization algorithms and their variants;
- Theoretical analysis (convergence, complexity, stability) of swarm‑intelligence optimizers;
- Hybrid swarm‑intelligence and machine learning frameworks;
- Sparse optimization based on swarm intelligence;
- Multi‑objective, many‑objective swarm intelligence optimization;
- Swarm intelligence for neural network training and hyper‑parameter tuning;
- Real‑world engineering and industrial applications of swarm‑based optimization;
- Benchmark testing and performance evaluation of swarm intelligence algorithms.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere. All manuscripts will go through the standard peer‑review procedure of the journal Mathematics. We sincerely invite researchers to contribute their original work to this Special Issue.
Prof. Dr. Qinwei Fan
Guest Editor
Manuscript Submission Information
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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-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Mathematics is an international peer-reviewed open access semimonthly 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 2600 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
- swarm intelligence
- metaheuristic optimization
- swarm-based algorithm
- machine learning
- sparse optimization
- real world applications
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