DocumentCode
2840158
Title
Quantum-Behaved Particle Swarm Optimization with Normal Cloud Mutation Operator
Author
Zhao, Ji ; Sun, Jun ; Xu, Wenbo
Author_Institution
Sch. of Inf. Technol., JiangNan Univ., Wuxi, China
fYear
2009
fDate
11-13 Dec. 2009
Firstpage
1
Lastpage
4
Abstract
The mutation mechanism is introduced into Quantum-behaved Particle Swarm Optimization to increase its global search ability and escape from local minima. Based on the properties of randomness and stable tendency of normal cloud model, this paper proposed a Quantum-behaved Particle Swarm Optimization with Normal Cloud Mutation Operator (QPSO-NCM). This method is tested and compared with particle swarm optimization (PSO), PSO-NCM and QPSO. The experimental results show that QPSO-NCM performs better than the others algorithms.
Keywords
particle swarm optimisation; global search ability; local minima; normal cloud model; normal cloud mutation operator; quantum behaved particle swarm optimization; Clouds; Convergence; Equations; Evolutionary computation; Genetic mutations; Information technology; Particle swarm optimization; Quantum computing; Sun; Testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence and Software Engineering, 2009. CiSE 2009. International Conference on
Conference_Location
Wuhan
Print_ISBN
978-1-4244-4507-3
Electronic_ISBN
978-1-4244-4507-3
Type
conf
DOI
10.1109/CISE.2009.5364714
Filename
5364714
Link To Document