DocumentCode :
51748
Title :
A Quantum-Based Particle Swarm Optimization Algorithm Applied to Inverse Problems
Author :
Ho, S.L. ; Shiyou Yang ; Guangzheng Ni ; Jin Huang
Author_Institution :
Dept. of Electr. Eng., Hong Kong Polytech. Univ., Hong Kong, China
Volume :
49
Issue :
5
fYear :
2013
fDate :
May-13
Firstpage :
2069
Lastpage :
2072
Abstract :
To balance exploration and exploitation searches in order to prevent premature convergences in Particle Swarm Optimization (PSO) algorithms, an improved Quantum-based PSO (QPSO) algorithm is proposed with an ultimate goal of preserving the simplicities of available QPSOs. The improvements include the design of diversification and intensification phases, searching mechanisms and a strategy to shift away from the worst solutions. The proposed QPSO are compared to available optimizers on two case studies to showcase its merits.
Keywords :
inverse problems; particle swarm optimisation; quantum theory; QPSO algorithm; balance exploration; diversification phase; intensification phase; inverse problems; premature convergences; quantum-based PSO algorithm; quantum-based particle swarm optimization; Evolutionary algorithm; inverse problem; optimal design; particle swarm optimization;
fLanguage :
English
Journal_Title :
Magnetics, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9464
Type :
jour
DOI :
10.1109/TMAG.2013.2237760
Filename :
6514656
Link To Document :
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