A new particle swarm optimization algorithm and its numerical analysis

Authors:
Yuelin Gao;Fanfan Lei;Miaomiao Wang
Affiliations:
Institute of Information & System Science, North Ethnic University, Yinchuan;Institute of Information & System Science, North Ethnic University, Yinchuan;Institute of Information & System Science, North Ethnic University, Yinchuan
Venue:
ICSI'10 Proceedings of the First international conference on Advances in Swarm Intelligence - Volume Part I
Year:
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.