An adaptive hybrid ant colony optimization algorithm for solving Capacitated Vehicle Routing

被引：0
|
作者：
Peng, YuZhong [1 ]
Pan, Yonghua [1 ]
Qin, ZhengYou [1 ]
Li, DeYong [1 ]
机构：
[1] Guangxi TeachersEduc Univ, Coll Comp & Informat Engn, Nanning 530001, Peoples R China
来源：
PROCEEDINGS OF THE 2015 INTERNATIONAL INDUSTRIAL INFORMATICS AND COMPUTER ENGINEERING CONFERENCE | 2015年
关键词：
Ant Colony Algorithm; Capacitated Vehicle Routing Problem; Genetic Algorithm; pheromone matrix;
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 Algorithm has certain advantages in solving Capacitated Vehicle Routing Problem (CVRP), but there are still easy to fall into local optimum, the search speed etc. To overcome these problems this paper presents an adaptive hybrid Ant colony optimization algorithm for solving Capacitated Vehicle Routing Problem. The adaptive hybrid ant colony optimization algorithm uses genetic algorithms to adjust pheromone matrix algorithm, and designs an adaptive pheromone evaporation rate adjustment strategies, and uses local search strategies to reduce the amount of calculation. Experiment on Some classic problems shows that the presented algorithm for solving the Capacitated Vehicle Routing Problem is effective and has better performance.
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页码：577 / 580
页数：4
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