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