A new approach of ant colony algorithm and its proof of convergence

被引：0
|
作者：
Zuo, Hong-hao [1 ]
Xiong, Fan-lun [2 ]
机构：
[1] Univ Sci & Technol China, Dept Automat, POB 1130, Hefei, Anhui Province, Peoples R China
[2] Chinese Acad Sci, Inst Intelligent Machines, Hefei, Anhui Province, Peoples R China
来源：
WCICA 2006: SIXTH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION, VOLS 1-12, CONFERENCE PROCEEDINGS | 2006年
关键词：
ant colony optimization algorithm; time model; convergence; traveling salesman problem;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
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.
引用
收藏
页码：3301 / +
页数：2
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