DocumentCode :
2728605
Title :
A new hybrid genetic algorithm based on chaos and PSO
Author :
Wang, Yiwen ; Yao, Min
Author_Institution :
Coll. of Comput. Sci. & Technol., Zhejiang Univ., Hangzhou, China
Volume :
1
fYear :
2009
fDate :
20-22 Nov. 2009
Firstpage :
699
Lastpage :
703
Abstract :
In practice, two key problems have been found in genetic algorithm (GA), one is premature convergence and the other is weak local search ability. In this paper, a new hybrid genetic algorithm based on chaos and particle swarm optimization (PSO) is proposed to solve the two problems above. The basic principle is that chaotic search mechanism and PSO mutation are added into the framework of simple genetic algorithm (SGA).By comparing the experimental results from five classic benchmark functions, the proposed genetic algorithm significantly improved both global convergence and convergence precision.
Keywords :
genetic algorithms; particle swarm optimisation; chaotic search mechanism; genetic algorithm; local search ability problem; particle swarm optimization; premature convergence problem; Chaos; Computer science; Convergence; Educational institutions; Equations; Fractals; Genetic algorithms; Genetic mutations; Logistics; Particle swarm optimization; Chaos; GA; PSO; Premature Convergence;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Computing and Intelligent Systems, 2009. ICIS 2009. IEEE International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-4754-1
Electronic_ISBN :
978-1-4244-4738-1
Type :
conf
DOI :
10.1109/ICICISYS.2009.5357766
Filename :
5357766
Link To Document :
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