Title :
Two Novel Particle Swarm Optimization Algorithm Models
Author :
Song, Shengli ; Kong, Li ; Cheng, Jingjing
Author_Institution :
Dept. of Comput. & Commun. Eng., Zhengzhou Univ. of Light Ind., Zhengzhou, China
Abstract :
According to the intelligent behavior of social population, two novel particle swarm algorithm optimization models are proposed by enhancing collaboration and information sharing capabilities of individuals. Benchmark function simulation results show the new algorithms, with both a better stability and a steady convergence, not only enhance the local searching efficiency and global searching performance greatly, but also have faster convergence speed and higher precision, and can avoid the premature convergence problem effectively.
Keywords :
particle swarm optimisation; search problems; information sharing; particle swarm optimization algorithm; social population intelligent behavior; Collaboration; Communication industry; Convergence; Cybernetics; Intelligent systems; Man machine systems; Optimization methods; Particle swarm optimization; Stability; Stochastic processes; Algorithm; Cooperation; Model; Particle Swarm Optimization;
Conference_Titel :
Intelligent Human-Machine Systems and Cybernetics, 2009. IHMSC '09. International Conference on
Conference_Location :
Hangzhou, Zhejiang
Print_ISBN :
978-0-7695-3752-8
DOI :
10.1109/IHMSC.2009.232