The Genetic Algorithm (GA) : Selection + Crossover + Mutation + Elitism
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
*******************************************************************************************************************************************
Cite As
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. Retrieved .
MATLAB Release Compatibility
Platform Compatibility
Windows macOS LinuxCategories
Tags
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!Discover Live Editor
Create scripts with code, output, and formatted text in a single executable document.
GA/
Version | Published | Release Notes | |
---|---|---|---|
1.0.0.0 | An update to the selection operator (Roulette wheel) to handle negative fitness values too. |