Title :
Cloud Estimation of Distribution Particle Swarm Optimizer
Author :
Gao, Ying ; Hu, Xiao ; Liu, Huiliang ; Li, Fufang
Author_Institution :
Dept. of Comput. Sci. & Technol., Guangzhou Univ., Guangzhou, China
Abstract :
Cloud estimation of distribution particle swarm optimizer combining PSO and cloud model is introduced. In the algorithm´s offspring generation scheme, new particles are generated in the cloud estimation of distribution way or in the PSO way. The innovation of the algorithm is production of cloud particles according to the cloud model theory. The cognitive population obtained during optimization is used to estimate statistical characteristics of good solution regions by backward cloud generator. And then the estimated statistical characteristics are used to produce cloud particles by positive cloud generator. Both the global information from cloud particles and local information from PSO particles are used to guide the further search. The proposed algorithm is applied to some well-known benchmarks. The experimental results show that the algorithm has stronger global search ability than original version of PSO.
Keywords :
cognitive systems; particle swarm optimisation; search problems; statistical analysis; backward cloud generator; cloud estimation; cloud model theory; cognitive population; distribution particle swarm optimizer; global search ability; offspring generation scheme; statistical characteristics; Algorithm design and analysis; Entropy; Generators; Helium; Optimization; Particle swarm optimization; Signal processing algorithms; Backward cloud generator; Cloud model; PSO; Positive cloud generator;
Conference_Titel :
Genetic and Evolutionary Computing (ICGEC), 2010 Fourth International Conference on
Conference_Location :
Shenzhen
Print_ISBN :
978-1-4244-8891-9
Electronic_ISBN :
978-0-7695-4281-2
DOI :
10.1109/ICGEC.2010.12