DocumentCode
2912902
Title
A cooperative artificial immune network with particle swarm behavior for multimodal function optimization
Author
Liu, Li ; Xu, Wenbo
Author_Institution
Inf. Technol. Dept., Jiangnan Univ., Wuxi
fYear
2008
fDate
1-6 June 2008
Firstpage
1550
Lastpage
1555
Abstract
Artificial immune network has been receiving particular attention over the last few years. Recent researches have revealed that, without stimulation and cooperation of network cells, lots of redundant explorations waste ldquoresourcesrdquo, which affects searching ability and searching speed. In this paper, a cooperative artificial immune network denoted CoAIN is devised for multimodal function optimization. To explore and exploit searching space efficiently and effectively, the interactions within the network are not only suppression but also cooperation. Network cells cooperate with particle swarm behavior making use of the best position encountered by itself and its neighbor. Numeric benchmark functions were used to assess the performance of CoAIN compared with opt-aiNet, BCA, hybrid GA, and PSO algorithms.
Keywords
artificial immune systems; particle swarm optimisation; search problems; PSO algorithms; cooperative artificial immune network; multimodal function optimization; particle swarm behavior; searching ability; searching speed; Artificial immune systems; Benchmark testing; Clustering algorithms; Convergence; Genetic algorithms; Genetic mutations; Immune system; Information technology; Particle swarm optimization; Size control;
fLanguage
English
Publisher
ieee
Conference_Titel
Evolutionary Computation, 2008. CEC 2008. (IEEE World Congress on Computational Intelligence). IEEE Congress on
Conference_Location
Hong Kong
Print_ISBN
978-1-4244-1822-0
Electronic_ISBN
978-1-4244-1823-7
Type
conf
DOI
10.1109/CEC.2008.4630998
Filename
4630998
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