Hybrid Particle Swarm Optimization and Gravitational Search Algorithm (PSOGSA)

PSOGSA is the efficient combination of PSO and GSA.
Updated 22 May 2018

View License

A new hybrid population-based algorithm (PSOGSA) is proposed with the combination of Particle Swarm Optimization (PSO) and Gravitational Search Algorithm (GSA). The main idea is to integrate the ability of exploitation in PSO with the ability of exploration in GSA to synthesize both algorithms’ strength. Some benchmark test functions are used to compare the hybrid algorithm with both the standard PSO and GSA algorithms in evolving best solution.
Paper: A New Hybrid PSOGSA Algorithm for Function Optimization, in IEEE International Conference on Computer and Information Application(ICCIA 2010), China, 2010, pp.374-377, DOI: http://dx.doi.org/10.1109/ICCIA.2010.6141614

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). Hybrid Particle Swarm Optimization and Gravitational Search Algorithm (PSOGSA) (https://www.mathworks.com/matlabcentral/fileexchange/35939-hybrid-particle-swarm-optimization-and-gravitational-search-algorithm-psogsa), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2008a
Compatible with any release
Platform Compatibility
Windows macOS Linux
Find more on Optimization Toolbox in Help Center and MATLAB Answers

Community Treasure Hunt

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

Start Hunting!
Version Published Release Notes

Typo fixed
There was an error when running the algorithm on F17 which have been resolved. PSOGSA is now able to solve problems which have variables with different ranges.