DocumentCode :
2831615
Title :
Quantum-behaved particle swarm optimization with mutation operator
Author :
Liu, Author Jing ; Xu, Author Wenbo ; Sun, Author Jun
Author_Institution :
Sch. of Inf. Technol., Southern Yangtze Univ., Wuxi
fYear :
2005
fDate :
16-16 Nov. 2005
Lastpage :
240
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 characteristic of QPSO algorithm, the variable of gbest and mbest is mutated with Cauchy distribution respectively. The experimental results on test functions show that QPSO with gbest and mbest mutation both performs better than PSO and QPSO without mutation
Keywords :
mathematical operators; particle swarm optimisation; search problems; statistical distributions; Cauchy distribution; global search ability; mutation operator; quantum-behaved particle swarm optimization; Birds; Convergence; Electronic mail; Evolutionary computation; Genetic mutations; Information technology; Particle swarm optimization; Performance evaluation; Sun; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Tools with Artificial Intelligence, 2005. ICTAI 05. 17th IEEE International Conference on
Conference_Location :
Hong Kong
ISSN :
1082-3409
Print_ISBN :
0-7695-2488-5
Type :
conf
DOI :
10.1109/ICTAI.2005.104
Filename :
1562943
Link To Document :
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