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

This is the implementation of the original version of the genetic algorithm
ダウンロード: 7.6K
更新 2018/6/11

ライセンスの表示

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

引用

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. 取得済み .

MATLAB リリースの互換性
作成: R2016b
すべてのリリースと互換性あり
プラットフォームの互換性
Windows macOS Linux
カテゴリ
Help Center および MATLAB AnswersGenetic Algorithm についてさらに検索

Community Treasure Hunt

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

Start Hunting!
バージョン 公開済み リリース ノート
1.0.0.0

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