An improved ant colony algorithm with biological characteristics

Qin Ling; Chen Yixin; Chen Ling; Wu Yan

An improved ant colony algorithm with biological characteristics

Qin Ling
, Chen Yixin
, Chen Ling
, Wu Yan

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

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.

Original language	English
Title of host publication	2006 IEEE International Conference on Granular Computing
Pages	405-408
Number of pages	4
State	Published - 2006
Event	2006 IEEE International Conference on Granular Computing - Atlanta, GA, United States Duration: May 10 2006 → May 12 2006

Publication series

Name	2006 IEEE International Conference on Granular Computing

Conference

Conference	2006 IEEE International Conference on Granular Computing
Country/Territory	United States
City	Atlanta, GA
Period	05/10/06 → 05/12/06

Keywords

Ant colony algorithm
Optimization

Cite this

@inproceedings{c5809d7817054e018e48c1cd28d74f04,

title = "An improved ant colony algorithm with biological characteristics",

abstract = "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.",

keywords = "Ant colony algorithm, Optimization",

author = "Qin Ling and Chen Yixin and Chen Ling and Wu Yan",

year = "2006",

language = "English",

isbn = "1424401348",

series = "2006 IEEE International Conference on Granular Computing",

pages = "405--408",

booktitle = "2006 IEEE International Conference on Granular Computing",

note = "2006 IEEE International Conference on Granular Computing ; Conference date: 10-05-2006 Through 12-05-2006",

}

TY - GEN

T1 - An improved ant colony algorithm with biological characteristics

AU - Ling, Qin

AU - Yixin, Chen

AU - Ling, Chen

AU - Yan, Wu

PY - 2006

Y1 - 2006

N2 - 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.

AB - 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.

KW - Ant colony algorithm

KW - Optimization

UR - https://www.scopus.com/pages/publications/33751114674

M3 - Conference contribution

AN - SCOPUS:33751114674

SN - 1424401348

SN - 9781424401345

T3 - 2006 IEEE International Conference on Granular Computing

SP - 405

EP - 408

BT - 2006 IEEE International Conference on Granular Computing

T2 - 2006 IEEE International Conference on Granular Computing

Y2 - 10 May 2006 through 12 May 2006

ER -

An improved ant colony algorithm with biological characteristics

Abstract

Publication series

Conference

Keywords

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Cite this