An improved ant colony algorithm with biological characteristics

被引：0

作者：

Qin, Ling ^{[1
]}

Chen, Yixin ^{[2
]}

Chen, Ling

Wu, Yan

机构：

[1] Nanjing Univ Aeronaut & Astronaut, Dept Comp Sci, Nanjing 210093, Peoples R China

[2] Univ Washington, Dept Comp Sci & Engn, Seattle, WA 63130 USA

来源：

2006 IEEE INTERNATIONAL CONFERENCE ON GRANULAR COMPUTING | 2006年

关键词：

ant colony algorithm; optimization;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

An improved ant colony algorithm with biological characteristics is proposed to guarantee the solution diversity of the algorithm. In the optimization process of the algorithm, the pheromone is updated by the biological diversity and quality of the solutions to obtain diversified solutions. Experimental results on the traveling salesman problem show that our algorithm have high convergence speed and can get diversified solutions, it succeeds avoiding the stagnation and premature problem.

引用

页码：405 / +

页数：2

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