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

This is the implementation of the original version of the genetic algorithm
Updated 11 Jun 2018

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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
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Cite As

Seyedali Mirjalili (2024). The Genetic Algorithm (GA) : Selection + Crossover + Mutation + Elitism (, MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2016b
Compatible with any release
Platform Compatibility
Windows macOS Linux

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Version Published Release Notes

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