DocumentCode :
1687719
Title :
Simulated annealing artificial fish swarm algorithm
Author :
Jiang, Mingyan ; Cheng, Yongming
Author_Institution :
Sch. of Inf. Sci. & Eng., Shandong Univ., Jinan, China
fYear :
2010
Firstpage :
1590
Lastpage :
1593
Abstract :
This paper presents a novel stochastic approach called the simulated annealing-artificial fish swarm algorithm (SA-AFSA) for solving some multimodal problems. The proposed algorithm incorporates the simulated annealing (SA) into artificial fish swarm algorithm (AFSA) to improve the performance of the AFSA. The hybrid algorithm has the following features: the hybrid algorithm maintains 1) the strong local searching ability of the SA and 2) the swarm intelligence of AFSA. The experimental results indicate that in all the test cases, the SA-AFSA can obtain much better optimization precision and the convergence speed compared with AFSA.
Keywords :
simulated annealing; artificial fish swarm algorithm; convergence speed; multimodal problems; optimization precision; simulated annealing; Algorithm design and analysis; Clustering algorithms; Marine animals; Particle swarm optimization; Signal processing algorithms; Simulated annealing; artificial fish swarm algorithm; data clustering; multimodal problem; simulated annealing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Control and Automation (WCICA), 2010 8th World Congress on
Conference_Location :
Jinan
Print_ISBN :
978-1-4244-6712-9
Type :
conf
DOI :
10.1109/WCICA.2010.5554452
Filename :
5554452
Link To Document :
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