DocumentCode :
1867846
Title :
An analysis of roulette selection in early particle swarm optimizing
Author :
Yang, Zhaofang ; Wang, Fang
Author_Institution :
Fac. of Comput. & Inf. Sci., Southwest Univ., Chongqing
fYear :
2006
fDate :
19-21 Jan. 2006
Lastpage :
970
Abstract :
In this paper, we present a novel particle swarm optimizer combined with the roulette selection operator. The modified algorithm provides a mechanism to restrain super particles in early stage and can effectively avoid the premature problem. It is empirically tested and compared with other published methods on several famous benchmark functions. The computational results illustrate that the proposed algorithm has the potential to achieve higher success ratio and better solution quality, especially for multimodal function optimization
Keywords :
artificial intelligence; genetic algorithms; particle swarm optimisation; benchmark functions; genetic algorithm; multimodal function optimization; particle swarm optimizer; roulette selection operator; solution quality; super particles restraint; Algorithm design and analysis; Benchmark testing; Biological system modeling; Biology computing; Birds; Computational intelligence; Computational modeling; Discrete event simulation; Optimization methods; Particle swarm optimization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Systems and Control in Aerospace and Astronautics, 2006. ISSCAA 2006. 1st International Symposium on
Conference_Location :
Harbin
Print_ISBN :
0-7803-9395-3
Type :
conf
DOI :
10.1109/ISSCAA.2006.1627485
Filename :
1627485
Link To Document :
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