Chaos Game Optimization (CGO)

Version 1.0.0 (2,09 KB) von Siamak Talatahari

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

Verfolgen

4.3

(3)

778 Downloads

Aktualisiert 6. Dez 2020

Lizenz anzeigen

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

Zitieren als

Siamak Talatahari (2024). Chaos Game Optimization (CGO) (https://www.mathworks.com/matlabcentral/fileexchange/83938-chaos-game-optimization-cgo), MATLAB Central File Exchange. Abgerufen28. November 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.

Mehrere Stile anzeigen

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.

Mehrere Stile anzeigen

Kompatibilität der MATLAB-Version

Erstellt mit R2020b

Kompatibel mit allen Versionen

Plattform-Kompatibilität

Windows macOS Linux

Tags Tags hinzufügen

Community Treasure Hunt

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

Start Hunting!

CGO.m

Version	Veröffentlicht	Versionshinweise
1.0.0	6. Dez 2020		Herunterladen

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} }