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Minimizing the Himmelblau Function using GA and PSO

version 2.0.0.0 (14.1 MB) by Karl Ezra Pilario
Genetic algorithm (GA) and Particle Swarm Optimization (PSO) for minimizing a multi-modal function

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Updated 20 Aug 2020

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This submission contains standard implementations of GA and PSO for minimizing the Himmelblau function. This function has 2 decision variables and is mutli-modal, i.e. it has 4 known minima within the bounds [-5, 5]. Thus, the answer would be any one among the 4 minima, and is different each time the codes are run.

The outputs of PSOHimmel.m and GAHimmel.m are:
1. Plot of worst, average, and best solutions against the elapsed iterations.
2. Plot of all candidates as a moving scatter plot on the search space.
3. Global minima where the run has converged.

Cite As

Karl Ezra Pilario (2020). Minimizing the Himmelblau Function using GA and PSO (https://www.mathworks.com/matlabcentral/fileexchange/65811-minimizing-the-himmelblau-function-using-ga-and-pso), MATLAB Central File Exchange. Retrieved .

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MATLAB Release Compatibility
Created with R2020a
Compatible with any release
Platform Compatibility
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