DocumentCode
1897314
Title
A Kind of Negative Feedback ACO Algorithm Based on Minimum Distance Balance Factor
Author
Shao, Xiaolu ; Yang, Aiping ; Dai, Wenzhan
Author_Institution
Dept. of Autom., Zhejiang Sci-Tech Univ., Hangzhou, China
Volume
1
fYear
2009
fDate
10-11 Oct. 2009
Firstpage
127
Lastpage
129
Abstract
The traditional ACO (ant colony optimization) needs quite a long time to converge and is prone to loop into a standstill in the optimization process of TSP (traveling salesman problem). In this paper, one kind of negative feedback ACO on minimum distance balance factor is proposed. Simulation results show its very effectiveness. Compared with the traditional ACO, the negative feedback ACO can greatly improve the probability of gaining the best solution from 25.6% to 41.6%.
Keywords
convergence; greedy algorithms; probability; travelling salesman problems; TSP; ant colony optimization; convergence; greedy algorithm; minimum distance balance factor; negative feedback ACO algorithm; probability; traveling salesman problem; Ant colony optimization; Automation; Convergence; Fellows; Finance; Greedy algorithms; Negative feedback; Negative feedback loops; Traveling salesman problems; ACO; Minimum Distance Balance Factor; Negative Feedback;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Computation Technology and Automation, 2009. ICICTA '09. Second International Conference on
Conference_Location
Changsha, Hunan
Print_ISBN
978-0-7695-3804-4
Type
conf
DOI
10.1109/ICICTA.2009.39
Filename
5287693
Link To Document