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