Intelligent Learning Ant Colony Algorithm

被引：2
|
作者：
Ma Jianhua [1 ]
Tian Fazhong [1 ]
机构：
[1] Shandong Econ Univ, Sch Informat Management, Jinan 250014, Peoples R China
来源：
MEASURING TECHNOLOGY AND MECHATRONICS AUTOMATION, PTS 1 AND 2 | 2011年 / 48-49卷
关键词：
ant colony algorithm; Intelligent ant colony; learning mechanism; TSP;
D O I：
10.4028/www.scientific.net/AMM.48-49.625
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
Ant colony algorithm is effective algorithm for NP-hard problems, but it also tends to mature early as other evolutionary algorithms. One improvement method of ant colony algorithm is studied in this paper. Intelligent learning ant colony algorithm with the pheromone difference and positive-negative learning mechanism is brought forward to solve TSP. The basic approach of ant colony algorithm is introduced firstly, then we introduced the individual pheromone matrix and positive-negative learning mechanism into ant colony algorithm. Next the steps of intelligent learning ant colony algorithm are given. At last the effectiveness of this algorithm is proved by random numerical examples and typical numerical examples. It is also proved that intelligent ant and learning mechanism will affect concentration degree of pheromone.
引用
收藏
页码：625 / 631
页数：7
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