A New Approach of Ant Colony Algorithm and Its Proof of Convergence

Author

Zuo, Hong-hao ; Xiong, Fan-lun

Author_Institution

Dept. of Autom., Univ. of Sci. & Technol. of China, He Fei

Volume

1

fYear

0

fDate

0-0 0

Firstpage

3301

Lastpage

3304

Abstract

Ant colony optimization algorithm, which is based on bionics, has been successfully used in many fields, especially on combinatorial optimization problems. While many parameters need to be adjusted in its application, it is inconvenient for rookies. A novel ant colony optimization algorithm based on real time model is proposed and its proof of convergence is given. It is supposed that each ant´s velocity is the same and all ants are crawling in full time. Ants communicate with others by the pheromone that is left on the road. After some time the ants trail will be on the optimal route between the food and the nest. It is testified by the experiment that the novel algorithm is as well as other ant colony algorithm and it is simpler to justify the parameters than before

Keywords

artificial intelligence; biocybernetics; convergence; travelling salesman problems; ant colony optimization algorithm; bionics; combinatorial optimization problems; convergence; pheromone; traveling salesman problem; Ant colony optimization; Automation; Concurrent computing; Convergence; Feedback; Helium; Machine intelligence; Roads; Testing; Traveling salesman problems; Ant colony optimization algorithm; convergence; time model; traveling salesman problem;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on

Conference_Location

Dalian

Print_ISBN

1-4244-0332-4

Type

conf

DOI

10.1109/WCICA.2006.1712978

Filename

1712978