The Genetic Algorithm (GA) : Selection + Crossover + Mutation + Elitism

This is the implementation of the original version of the genetic algorithm
7,6K download
Aggiornato 11 giu 2018

Visualizza la licenza

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
*******************************************************************************************************************************************

Cita come

Seyedali Mirjalili (2024). The Genetic Algorithm (GA) : Selection + Crossover + Mutation + Elitism (https://www.mathworks.com/matlabcentral/fileexchange/67435-the-genetic-algorithm-ga-selection-crossover-mutation-elitism), MATLAB Central File Exchange. Recuperato .

Compatibilità della release di MATLAB
Creato con R2016b
Compatibile con qualsiasi release
Compatibilità della piattaforma
Windows macOS Linux

Community Treasure Hunt

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

Start Hunting!
Versione Pubblicato Note della release
1.0.0.0

An update to the selection operator (Roulette wheel) to handle negative fitness values too.