Multiobjective Firefly Algorithm (MOFA)

Versión 2.0.0 (6,35 KB) por XS Yang

This demo shows how the multiobjective firefly algorithm (MOFA) works.

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The multiobjective firefly algorithm (MOFA) is a nature-inspired optimization algorithm. This demo solves the bi-objective ZDT3 functions with D=30 (dimensions), and the obtained Pareto Front is displayed. It is relatively straightforward to extend this code to solve other multi-objective functions and optimization problems. You can change the objective functions, the dimensionality, and simple lower and upper bounds (Lb, Ub). Some parameter tuning to vary parameters slightly (such as theta, gamma, and number of iterations) may help improve the quality of the solutions.

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XS Yang (2024). Multiobjective Firefly Algorithm (MOFA) (https://www.mathworks.com/matlabcentral/fileexchange/74755-multiobjective-firefly-algorithm-mofa), MATLAB Central File Exchange. Recuperado 21 noviembre, 2024.

Yang, Xin-She. “Multiobjective Firefly Algorithm for Continuous Optimization.” Engineering with Computers, vol. 29, no. 2, Springer Science and Business Media LLC, Jan. 2012, pp. 175–84, doi:10.1007/s00366-012-0254-1.

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Versión	Publicado	Notas de la versión
2.0.0	29 mar 2020	Updated version.	Descargar
1.0.0	29 mar 2020		Descargar

MLA	Yang, Xin-She. “Multiobjective Firefly Algorithm for Continuous Optimization.” Engineering with Computers, vol. 29, no. 2, Springer Science and Business Media LLC, Jan. 2012, pp. 175–84, doi:10.1007/s00366-012-0254-1.
APA	Yang, X.-S. (2012). Multiobjective firefly algorithm for continuous optimization. Engineering with Computers, 29(2), 175–184. Springer Science and Business Media LLC. Retrieved from https://doi.org/10.1007%2Fs00366-012-0254-1
BibTeX	@article{Yang_2012, doi = {10.1007/s00366-012-0254-1}, url = {https://doi.org/10.1007%2Fs00366-012-0254-1}, year = 2012, month = {jan}, publisher = {Springer Science and Business Media {LLC}}, volume = {29}, number = {2}, pages = {175--184}, author = {Xin-She Yang}, title = {Multiobjective firefly algorithm for continuous optimization}, journal = {Engineering with Computers} }