The Novel Parameter Selection of Particle Swarm Optimization

Zhuo Li; Xue Luo Qu

doi:10.4028/www.scientific.net/AMR.479-481.344

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 479-481The Novel Parameter Selection of Particle Swarm...

The Novel Parameter Selection of Particle Swarm Optimization

Abstract:

Particle Swarm Optimization (PSO) is a novel artificial intelligent technique proposed by Eberhart and Kennedy which is a type of Swarm Intelligence. PSO is simulated as population-based stochastic optimization influenced by the social behavior of bird flocks. In past decades, more and more researcher has been targeting to improve the original PSO for solving various problems and it has great potential to be done further. This paper reviews the progress of PSO research so far, and the recent achievements for application to large-scale optimization problems.

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Periodical:

Advanced Materials Research (Volumes 479-481)

Pages:

344-347

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.479-481.344

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Online since:

February 2012

Authors:

Zhuo Li, Xue Luo Qu

Keywords:

Parameter, Particle Swarm Optimization Algorithm (PSO), Swarm Intelligence, Variants

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References

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