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A new particle swarm optimization algorithm and its numerical analysis

Yuelin Gao,Fanfan Lei, Miaomiao Wang

ADVANCES IN SWARM INTELLIGENCE, PT 1, PROCEEDINGS（2010）

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Abstract
The speed equation of particle swarm optimization is improved by using a convex combination of the current best position of a particle and the current best position which the whole particle swarm as well as the current position of the particle, so as to enhance global search capability of basic particle swarm optimization Thus a new particle swarm optimization algorithm is proposed Numerical experiments show that its computing time is short and its global search capability is powerful as well as its computing accuracy is high in compared with the basic PSO.
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Key words
particle swarm optimization,computing time,current position,computing accuracy,basic particle swarm optimization,current best position,basic pso,numerical analysis,new particle swarm optimization,global search capability,whole particle swarm,velocity equation,convex combination,particle swarm
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