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

Sparrowhawk Optimization Algorithm

Cited by 0Open access

Abstract

Swarm intelligence optimization algorithms, by simulating the collaborative behavior of biological groups in nature, exhibit strong global search capabilities in complex optimization problems. However, many existing algorithms are designed based on the assumptions that "the optimal solution is reliable" and "failed searches are invalid perturbations," thus ignoring the informational value inherent in perceptual uncertainty and erroneous decisions. To address this, this paper proposes a novel swarm intelligence optimization method—the Sparrowhawk Optimization Algorithm. This algorithm uses the hunting behavior of a sparrowhawk as a prototype, modeling the search process from aspects such as visual perception, dive path, and misjudgment correction. By introducing a visual credibility field, continuous dive path modeling, a misjudgment reverse gain mechanism, and a cognitive energy budget model, the Sparrowhawk Optimization Algorithm breaks through the traditional paradigms of "one-step update" and "absolutely reliable optimal solution," making the search process more dynamically adaptable and interpretable. This algorithm provides a new approach for constructing swarm intelligence optimization models with cognitive characteristics.

Cite this paper

APA 7

Zhang, J. (2026). Sparrowhawk Optimization Algorithm. Zenodo (CERN European Organization for Nuclear Research). https://doi.org/10.5281/zenodo.18366507

MLA 9

Zhang, Jincheng. “Sparrowhawk Optimization Algorithm.” Zenodo (CERN European Organization for Nuclear Research), 2026, https://doi.org/10.5281/zenodo.18366507.

Chicago

Zhang, Jincheng. 2026. “Sparrowhawk Optimization Algorithm.” Zenodo (CERN European Organization for Nuclear Research). https://doi.org/10.5281/zenodo.18366507.

Harvard

Zhang, J. (2026) ‘Sparrowhawk Optimization Algorithm’, Zenodo (CERN European Organization for Nuclear Research). Available at: https://doi.org/10.5281/zenodo.18366507.

BibTeX

@misc{zhang2026sparrowhawk,
  title = {{Sparrowhawk Optimization Algorithm}},
  author = {Zhang, Jincheng},
  journal = {Zenodo (CERN European Organization for Nuclear Research)},
  year = {2026},
  doi = {10.5281/zenodo.18366507}
}

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