DocumentCode
2146497
Title
An Improved Ant Colony Algorithm
Author
Zhang Xin ; Zhou Yu-zhong ; Fang Ping
Author_Institution
Dept. of Mathematic, South China Agriultural Univ., Guangzhou
fYear
2008
fDate
30-31 Dec. 2008
Firstpage
98
Lastpage
100
Abstract
Artificial ant colony algorithm is new in the evolution computing. The primary study shows it is a better algorithm with robust based population, but it has some shortcomings such as its slow computing speed, and it is easy to fall in local peak in large scale problem. To overcome these deficiencies, an improved ant colony algorithm is designed through abstracting the advantages of particle swarm optimization (PSO).
Keywords
evolutionary computation; particle swarm optimisation; artificial ant colony algorithm; evolution computing; particle swarm optimization; Ant colony optimization; Cities and towns; Educational institutions; Finishing; Information technology; Mathematics; Multimedia computing; Particle swarm optimization; Robustness; Traveling salesman problems; Ant colony algorithmx; global optimization; local optimum; particle swarm optimination;
fLanguage
English
Publisher
ieee
Conference_Titel
MultiMedia and Information Technology, 2008. MMIT '08. International Conference on
Conference_Location
Three Gorges
Print_ISBN
978-0-7695-3556-2
Type
conf
DOI
10.1109/MMIT.2008.157
Filename
5089068
Link To Document