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 :
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