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
Link To Document :
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