Hybrid Particle Swarm Optimization and Gravitational Search Algorithm (PSOGSA)

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

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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

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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. Recuperado .

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Se creó con R2008a
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Versión Publicado Notas de la versión
1.4.0.0

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.

1.0.0.0