preprint · Zenodo (CERN European Organization for Nuclear Research) · 2025

Cobra Optimization Algorithm

Zhang, Jincheng

Cited by 0Open access

Abstract

This paper proposes an optimization algorithm inspired by cobra behavior—the Cobra Optimization Algorithm (COA). This algorithm leverages the cobra's hunting strategy, neck extension deterrent behavior, venom concentration adaptive mechanism, and group collaboration as its core inspiration to achieve an effective balance between local search and global exploration. This paper mathematically models the algorithm, deriving in detail the position update formula, local and global search mechanisms, group collaboration mechanism, and multimodal global search strategy. The algorithm's convergence and search characteristics are analyzed. This algorithm possesses unique biological behavior mapping capabilities and multimodal optimization potential, providing a new solution strategy for complex optimization problems.

Cite this paper

APA 7

Zhang, J. (2025). Cobra Optimization Algorithm. Zenodo (CERN European Organization for Nuclear Research). https://doi.org/10.5281/zenodo.17139169

MLA 9

Zhang, Jincheng. “Cobra Optimization Algorithm.” Zenodo (CERN European Organization for Nuclear Research), 2025, https://doi.org/10.5281/zenodo.17139169.

Chicago

Zhang, Jincheng. 2025. “Cobra Optimization Algorithm.” Zenodo (CERN European Organization for Nuclear Research). https://doi.org/10.5281/zenodo.17139169.

Harvard

Zhang, J. (2025) ‘Cobra Optimization Algorithm’, Zenodo (CERN European Organization for Nuclear Research). Available at: https://doi.org/10.5281/zenodo.17139169.

BibTeX

@misc{zhang2025cobra,
  title = {{Cobra Optimization Algorithm}},
  author = {Zhang, Jincheng},
  journal = {Zenodo (CERN European Organization for Nuclear Research)},
  year = {2025},
  doi = {10.5281/zenodo.17139169}
}

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