COA

A new metaheuristic for global optimization problems proposed in the IEEE Congress on Evolutionary Computation (CEC), 2018

https://github.com/jkpir/COA

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The Coyote Optimization Algorithm (COA) is a nature-inspired metaheuristic for global optimization proposed by Juliano Pierezan and Leandro dos Santos Coelho (2018).

Matlab version available on: https://www.mathworks.com/matlabcentral/fileexchange/68373-coa

Python and R versions available on: https://github.com/jkpir/COA

Original publication:
Pierezan, J. and Coelho, L. S. "Coyote Optimization Algorithm: A new metaheuristic for global optimization problems", Proceedings of the IEEE Congress on Evolutionary Computation (CEC), Rio de Janeiro, Brazil, July 2018, pages 2633-2640.
https://ieeexplore.ieee.org/document/8477769

Juliano Pierezan
https://www.linkedin.com/in/pierezanj
https://www.researchgate.net/profile/Juliano_Pierezan
https://scholar.google.com.br/citations?user=6S89BfgAAAAJ

Leandro dos Santos Coelho
https://www.linkedin.com/in/leandro-dos-santos-coelho-54559214/
https://www.researchgate.net/profile/Leandro_Coelho
https://scholar.google.com/citations?user=0X7VkC4AAAAJ&hl=en

Cite As

Juliano Pierezan (2026). COA (https://github.com/jkpir/COA), GitHub. Retrieved .

Pierezan, J. and Coelho, L. S. "Coyote Optimization Algorithm: A new metaheuristic for global optimization problems", Proceedings of the IEEE Congress on Evolutionary Computation (CEC), Rio de Janeiro, Brazil, July 2018, pages 2633-2640.

General Information

MATLAB Release Compatibility

  • Compatible with any release

Platform Compatibility

  • Windows
  • macOS
  • Linux

Versions that use the GitHub default branch cannot be downloaded

Version Published Release Notes Action
1.0.6

New publications.

1.0.5

R version available.

1.0.4

The Python version has been add to the repository.

1.0.3

Github integration.

1.0.2

The publication's link (IEEE Xplore Digital Library) has been added to the description.

1.0.1

The description has been updated.

1.0.0

To view or report issues in this GitHub add-on, visit the GitHub Repository.
To view or report issues in this GitHub add-on, visit the GitHub Repository.