Artificial Fish School Algorithm for Function Optimization

Function optimization is always being one of the important problems of scientific field. Over the past a few decades, many artificial intelligent optimizing algorithms have been invented, such as genetic algorithm (GA), ant colony optimization (ACO), particle swarm optimization (PSO), and so on. Art...

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Bibliographic Details
Published in2010 2nd International Conference on Information Engineering and Computer Science pp. 1 - 4
Main Authors Jie Hu, Xiangjin Zeng, Jiaqing Xiao
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.12.2010
Subjects
Educational institutions
Gallium
Marine animals
Optimization
Particle swarm optimization
Robustness
Visualization
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Summary:Function optimization is always being one of the important problems of scientific field. Over the past a few decades, many artificial intelligent optimizing algorithms have been invented, such as genetic algorithm (GA), ant colony optimization (ACO), particle swarm optimization (PSO), and so on. Artificial fish school algorithm (AFSA) is a novel optimizing method. In this paper, AFSA was applied to function optimization and was compared with the above three methods. Experimental simulations show that the AFSA can find the global optimum more accurately.
ISBN:1424479398
9781424479399
ISSN:2156-7379
DOI:10.1109/ICIECS.2010.5678350