NDLI: A New Cellular Automata-Based Mixed Cellular Ant Algorithm for Solving Continuous System Optimization Programs

Content Provider	IEEE Xplore Digital Library
Author	Tingsong Du Pusheng Fei Jigui Jian
Copyright Year	2008
Description	Author affiliation: Coll. of Math. & Comput. Sci., Wuhan Univ., Wuhan (Pusheng Fei) \|\| Inst. of Nonlinear & Complex Syst., China Three Gorges Univ., Yichang (Tingsong Du; Jigui Jian)
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.
Starting Page	407
Ending Page	411
File Size	660806
Page Count	5
File Format	PDF
ISBN	9780769533049
DOI	10.1109/ICNC.2008.393
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-10-18
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Algorithm design and analysis Constraint optimization Ant colony optimization Space technology Continuous time systems Educational institutions Electronic mail Mathematical model MATLAB Testing
Content Type	Text
Resource Type	Article

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