Adaptive particle swarm optimization on individual level
Xiao-Feng Xie
Wen-Jun Zhang
Zhi-Lian Yang
Inst. of Microelectron., Tsinghua Univ., Beijing, China;
This paper appears in: Signal Processing, 2002 6th International Conference on
Publication Date: 26-30 Aug. 2002
Volume: 2,
On page(s): 1215- 1218 vol.2
ISSN:
ISBN: 0-7803-7488-6
INSPEC Accession Number: 7720859
Current Version Published: 2003-02-28
Abstract
An adaptive particle swarm optimization (PSO) on individual level is presented. By analyzing the social model of PSO, a replacement criterion, based on the diversity of fitness between the current particle and the best historical experience, is introduced to maintain the social attribution of swarm adaptively by taking off inactive particles. The testing of three benchmark functions indicates that it improves the average performance effectively.
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