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10

GECCO
2003
Springer

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130views Optimization» more GECCO 2003»

A New Approach to Improve Particle Swarm Optimization

13 years 9 months ago

A New Approach to Improve Particle Swarm Optimization

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Abstract. Particle swarm optimization (PSO) is a new evolutionary computation technique. Although PSO algorithm possesses many attractive properties, the methods of selecting inertia weight need to be further investigated. Under this consideration, the inertia weight employing random number uniformly distributed in [0,1] was introduced to improve the performance of PSO algorithm in this work. Three benchmark functions were used to test the new method. The results were presented to show that the new method is effective.

Liping Zhang, Huanjun Yu, Shangxu Hu

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GECCO 2003 | Inertia Weight | Particle Swarm Optimization | PSO Algorithm |

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Added	06 Jul 2010
Updated	06 Jul 2010
Type	Conference
Year	2003
Where	GECCO
Authors	Liping Zhang, Huanjun Yu, Shangxu Hu

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