DocumentCode :
1752862
Title :
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
Link To Document :
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