Chaos Game Optimization (CGO)

Versione 1.0.0 (2,09 KB) da Siamak Talatahari

The Chaos Game Optimization (CGO) algorithm is a simple however efficient optimization meta-heuristic presented. The main concept of the CGO

Segui

4.0

(2)

721 download

Aggiornato 6 dic 2020

Visualizza la licenza

The Chaos Game Optimization (CGO) algorithm is a simple however efficient optimization meta-heuristic presented. The main concept of the CGO algorithm is based on some principles of chaos theory in which the configuration of fractals by chaos game methodology alongside the fractals self-similarity issues are in perspective.
Author and programmer: S. Talatahari, M. Azizi, Email: Siamak.Talat@gmail.com, mehdi.azizi875@gmail.com
Main paper:
1. S. Talatahari, M. Azizi, Chaos Game Optimization: a Novel Metaheuristic Algorithm, Artificial Intelligence Review, 2020, https://doi.org/10.1007/s10462-020-09867-w
2. S. Talatahari, M. Azizi, Optimization of Constrained Mathematical and Engineering Design Problems Using Chaos Game Optimization, Computers & Industrial Engineering, Volume 145, Pages 106560, https://doi.org/10.1016/j.cie.2020.106560

Cita come

Siamak Talatahari (2024). Chaos Game Optimization (CGO) (https://www.mathworks.com/matlabcentral/fileexchange/83938-chaos-game-optimization-cgo), MATLAB Central File Exchange. Recuperato aprile 26, 2024.

Talatahari, Siamak, and Mahdi Azizi. “Chaos Game Optimization: a Novel Metaheuristic Algorithm.” Artificial Intelligence Review, Springer Science and Business Media LLC, June 2020, doi:10.1007/s10462-020-09867-w.

Visualizza più stili

Talatahari, Siamak, and Mahdi Azizi. “Optimization of Constrained Mathematical and Engineering Design Problems Using Chaos Game Optimization.” Computers & Industrial Engineering, vol. 145, Elsevier BV, July 2020, p. 106560, doi:10.1016/j.cie.2020.106560.

Visualizza più stili

Compatibilità della release di MATLAB

Creato con R2020b

Compatibile con qualsiasi release

Compatibilità della piattaforma

Windows macOS Linux

Tag Aggiungi tag

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

CGO.m

Versione	Pubblicato	Note della release
1.0.0	6 dic 2020		Scarica

MLA	Talatahari, Siamak, and Mahdi Azizi. “Chaos Game Optimization: a Novel Metaheuristic Algorithm.” Artificial Intelligence Review, Springer Science and Business Media LLC, June 2020, doi:10.1007/s10462-020-09867-w.
APA	Talatahari, S., & Azizi, M. (2020). Chaos Game Optimization: a novel metaheuristic algorithm. Artificial Intelligence Review. Springer Science and Business Media LLC. Retrieved from https://doi.org/10.1007%2Fs10462-020-09867-w
BibTeX	@article{Talatahari_2020, doi = {10.1007/s10462-020-09867-w}, url = {https://doi.org/10.1007%2Fs10462-020-09867-w}, year = 2020, month = {jun}, publisher = {Springer Science and Business Media {LLC}}, author = {Siamak Talatahari and Mahdi Azizi}, title = {Chaos Game Optimization: a novel metaheuristic algorithm}, journal = {Artificial Intelligence Review} }

MLA	Talatahari, Siamak, and Mahdi Azizi. “Optimization of Constrained Mathematical and Engineering Design Problems Using Chaos Game Optimization.” Computers & Industrial Engineering, vol. 145, Elsevier BV, July 2020, p. 106560, doi:10.1016/j.cie.2020.106560.
APA	Talatahari, S., & Azizi, M. (2020). Optimization of constrained mathematical and engineering design problems using chaos game optimization. Computers & Industrial Engineering, 145, 106560. Elsevier BV. Retrieved from https://doi.org/10.1016%2Fj.cie.2020.106560
BibTeX	@article{Talatahari_2020, doi = {10.1016/j.cie.2020.106560}, url = {https://doi.org/10.1016%2Fj.cie.2020.106560}, year = 2020, month = {jul}, publisher = {Elsevier {BV}}, volume = {145}, pages = {106560}, author = {Siamak Talatahari and Mahdi Azizi}, title = {Optimization of constrained mathematical and engineering design problems using chaos game optimization}, journal = {Computers {\&} Industrial Engineering} }