WCCI 2012 IEEE World Congress on Computational Intelligence , 2012-06-10

Title : ( A New Artificial Fish Swarm Algorithm for Dynamic Optimization Problems )

Authors: D. Yazdani , Mohammad Reza Akbarzadeh Totonchi , B. Nasiri , M. R. Meybodi ,

Citation: BibTeX | EndNote

Artificial fish swarm algorithm is one of the swarm intelligence algorithms which performs based on population and stochastic search contributed to solve optimization problems. This algorithm has been applied in various applications e.g. data clustering, neural networks learning, nonlinear function optimization, etc. Several problems in real world are dynamic and uncertain, which could not be solved in a similar manner of static problems. In this paper, for the first time, a modified artificial fish swarm algorithm is proposed in consideration of dynamic environments optimization. The results of the proposed approach were evaluated using moving peak benchmarks, which are known as the best metric for evaluating dynamic environments, and also were compared with results of several state-of-the-art approaches. The experimental results show that the performance of the proposed method outperforms that of other algorithms in this domain.

Keywords

dynamic optimization problems; artficial fish swarm algorithm; moving peaks benchmark; dynamic
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@inproceedings{paperid:1031324,
author = {D. Yazdani and Akbarzadeh Totonchi, Mohammad Reza and B. Nasiri and M. R. Meybodi},
title = {A New Artificial Fish Swarm Algorithm for Dynamic Optimization Problems},
booktitle = {WCCI 2012 IEEE World Congress on Computational Intelligence},
year = {2012},
location = {Brisbane, AUSTRALIA},
keywords = {dynamic optimization problems; artficial fish swarm algorithm; moving peaks benchmark; dynamic environments.},
}

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%0 Conference Proceedings
%T A New Artificial Fish Swarm Algorithm for Dynamic Optimization Problems
%A D. Yazdani
%A Akbarzadeh Totonchi, Mohammad Reza
%A B. Nasiri
%A M. R. Meybodi
%J WCCI 2012 IEEE World Congress on Computational Intelligence
%D 2012

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