A study about the improvement of Ant colony algorithm

被引：0
|
作者：
Liang Wen-zhe [1 ]
Niu Qing-yin [1 ]
Fan Chao [2 ]
机构：
[1] Acad Armored Force Engn, Dept Fundamental Courses, Beijing 100072, Peoples R China
[2] 900 Huangmei Bridge, Jurong City 212421, Jiangsu, Peoples R China
来源：
PROCEEDINGS OF THE 2015 4TH NATIONAL CONFERENCE ON ELECTRICAL, ELECTRONICS AND COMPUTER ENGINEERING ( NCEECE 2015) | 2016年 / 47卷
关键词：
ant colony algorithm; genetic algorithm; crossover operation;
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：
The ant colony algorithm is a new kind of simulated evolutionary algorithm for random searching, which converges to the optimal path by the accumulation of pheromone and updating. But it lacks the global searching ability, and easily falls into local minimum and appears the phenomenon of premature stagnation. In this paper, the improved method, which applies a stronger global searching ability of genetic algorithm and introduces the improved crossover and mutation operation, is designed to enhance the global searching ability of ant colony algorithm. The improved algorithm is applied to a two-dimensional function optimization simulation calculation. The results show that the improved ant colony algorithm is better than the original in accuracy and time efficiency
引用
收藏
页码：648 / 651
页数：4
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