preprint · Zenodo (CERN European Organization for Nuclear Research) · 2026

Silverfish Optimization Algorithm

Cited by 0Open access

Abstract

Swarm intelligence optimization algorithms solve complex optimization problems by simulating the collective behavior of organisms in nature. This paper proposes a novel swarm intelligence algorithm—the Silverfish Optimization Algorithm (SFOA)—inspired by the rapid swimming, environmental perception, and cooperative behavior of silverfish in humid environments. The algorithm achieves an efficient balance between global search and local development by introducing global random exploration, neighbor cooperation, local fine-tuning, environmental perception mechanisms, and swarm memory mechanisms. This paper details the algorithm modeling, mathematical formula description, iterative process, characteristic analysis, and application potential, and theoretically analyzes the algorithm's convergence and swarm intelligence characteristics. Results show that SFOA possesses strong global search capabilities, fine-tuning local optimization capabilities, dynamic adaptive characteristics, and good swarm cooperation effects, making it suitable for various continuous and combinatorial optimization problems.

Cite this paper

APA 7

Zhang, J. (2026). Silverfish Optimization Algorithm. Zenodo (CERN European Organization for Nuclear Research). https://doi.org/10.5281/zenodo.18184817

MLA 9

Zhang, Jincheng. “Silverfish Optimization Algorithm.” Zenodo (CERN European Organization for Nuclear Research), 2026, https://doi.org/10.5281/zenodo.18184817.

Chicago

Zhang, Jincheng. 2026. “Silverfish Optimization Algorithm.” Zenodo (CERN European Organization for Nuclear Research). https://doi.org/10.5281/zenodo.18184817.

Harvard

Zhang, J. (2026) ‘Silverfish Optimization Algorithm’, Zenodo (CERN European Organization for Nuclear Research). Available at: https://doi.org/10.5281/zenodo.18184817.

BibTeX

@misc{zhang2026silverfish,
  title = {{Silverfish Optimization Algorithm}},
  author = {Zhang, Jincheng},
  journal = {Zenodo (CERN European Organization for Nuclear Research)},
  year = {2026},
  doi = {10.5281/zenodo.18184817}
}

Made from the index record. Check names, capitalisation and page numbers against the paper. Need another style? AI for Research has over 10,000.