Tutorial: Genetic Algorithm and Particle Swarm Optimization

GA and PSO: Code with comments for understanding the algorithms.


Updated 19 May 2022

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This submission contains standard implementations of GA and PSO for minimizing various 2-D test functions. The code is intended for students who wish to learn GA and PSO code line by line. Users can change a few parameters to see the effects on the algorithm behavior.
The outputs of PSOtutor.m and GAtutor.m are:
  1. Simulation: Plot of all candidates as a moving scatter plot on the search space.
  2. Performance: Plot of worst, median, and best solutions against the elapsed iterations.
  3. Final Answer: Global minima where the run has converged.

Cite As

Karl Ezra Pilario (2023). Tutorial: Genetic Algorithm and Particle Swarm Optimization (https://www.mathworks.com/matlabcentral/fileexchange/65811-tutorial-genetic-algorithm-and-particle-swarm-optimization), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2022a
Compatible with any release
Platform Compatibility
Windows macOS Linux

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Version Published Release Notes

Added more test functions to minimize.

Revised code parts

Added PSO