DocumentCode :
3313219
Title :
A New Cellular Automata-Based Mixed Cellular Ant Algorithm for Solving Continuous System Optimization Programs
Author :
Du, Tingsong ; Fei, Pusheng ; Jian, Jigui
Author_Institution :
Inst. of Nonlinear & Complex Syst., China Three Gorges Univ., Yichang
Volume :
7
fYear :
2008
fDate :
18-20 Oct. 2008
Firstpage :
407
Lastpage :
411
Abstract :
Ant colony algorithm is a kind of bionic algorithm which sources from the behaviors of the ant colony. Based on the idea of ant algorithm and the principle of cellular automata, this paper develops a new mixed cellular ant algorithm and its mathematical description that can be used for solving the optimization programs of continuous systems. By using the method, the ideal searching direction of global optimal solution could be found as soon as possible. The algorithm is coded in MATLAB, and is tested through series of typical optimization problem instances. The experiment indicates that the improved and mixed cellular ant algorithm improves the efficiency of searching and veracity of result.
Keywords :
cellular automata; optimisation; MATLAB; ant colony algorithm; bionic algorithm; cellular automata; continuous system optimization programs; mixed cellular ant algorithm; Algorithm design and analysis; Ant colony optimization; Constraint optimization; Continuous time systems; Educational institutions; Electronic mail; MATLAB; Mathematical model; Space technology; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Natural Computation, 2008. ICNC '08. Fourth International Conference on
Conference_Location :
Jinan
Print_ISBN :
978-0-7695-3304-9
Type :
conf
DOI :
10.1109/ICNC.2008.393
Filename :
4668009
Link To Document :
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