Title :
An Adaptive Hybrid Particle Swarm Optimization
Author :
Liu, Yong ; Liang, Fangfang
Author_Institution :
Inst. of Intell. Vision & Image Inf., China Three Gorges Univ., Yichang, China
Abstract :
The particle swarm optimization (PSO) algorithm is vulnerable to reach local optimal value. So, this paper presents an adaptive hybrid particles swarm optimization. During the solving process, both crossover operator in genetic algorithm and hyper-mutation are introduced. Referring to the selection mechanism of immune algorithm based on information entropy, the adaptive selections mechanism is proposed. Experiments show that the algorithm effectively improves global search capability.
Keywords :
entropy; genetic algorithms; particle swarm optimisation; adaptive hybrid PSO algorithm; adaptive selection mechanism; crossover operator; genetic algorithm; hyper-mutation; immune algorithm; information entropy; particle swarm optimization; Algorithm design and analysis; Biological system modeling; Biology computing; Competitive intelligence; Computational intelligence; Convergence; Genetic algorithms; Immune system; Information entropy; Particle swarm optimization; Cross; Hyper-mutation; Particle Swarm Optimization Algorithm; immune algorithm based on information entropy;
Conference_Titel :
Computational Intelligence and Design, 2009. ISCID '09. Second International Symposium on
Conference_Location :
Changsha
Print_ISBN :
978-0-7695-3865-5
DOI :
10.1109/ISCID.2009.29
