Ahora está siguiendo esta publicación
- Verá actualizaciones en las notificaciones de contenido en seguimiento.
- Podrá recibir correos electrónicos, en función de las preferencias de comunicación que haya establecido.
This submission includes the main components of the Genetic Algorithm (GA) including Selection + Crossover + Mutation + Elitism. There are functions for each and the GA has been developed as a function as well. Of course, it is the discrete (binary) version of the GA algorithm since all the genes can be assigned with either 0 or 1.
More information can be found in www.alimirjalili.com
I have a number of relevant courses in this area. You can enrol via the following links with 95% discount:
*******************************************************************************************************************************************
A course on “Optimization Problems and Algorithms: how to understand, formulation, and solve optimization problems”:
https://www.udemy.com/optimisation/?couponCode=MATHWORKSREF
A course on “Introduction to Genetic Algorithms: Theory and Applications”
https://www.udemy.com/geneticalgorithm/?couponCode=MATHWORKSREF
*******************************************************************************************************************************************
Citar como
Seyedali Mirjalili (2026). The Genetic Algorithm (GA) : Selection + Crossover + Mutation + Elitism (https://es.mathworks.com/matlabcentral/fileexchange/67435-the-genetic-algorithm-ga-selection-crossover-mutation-elitism), MATLAB Central File Exchange. Recuperado .
Información general
- Versión 1.0.0.0 (5,29 KB)
Compatibilidad con la versión de MATLAB
- Compatible con cualquier versión
Compatibilidad con las plataformas
- Windows
- macOS
- Linux
| Versión | Publicado | Notas de la versión | Action |
|---|---|---|---|
| 1.0.0.0 | An update to the selection operator (Roulette wheel) to handle negative fitness values too. |
