DocumentCode
478025
Title
Application of Improved Ant Colony Algorithm
Author
Shi, Hongyan ; Bei, Zhaoyu
Author_Institution
Sch. of Inf. Sci. & Eng., Shenyang Univ. of Technol., Shenyang
Volume
1
fYear
2008
fDate
18-20 Oct. 2008
Firstpage
284
Lastpage
288
Abstract
A stochastic optimization algorithm is proposed by combining ant colony (ACO) algorithm with artificial fish-swarm algorithm (AFSA) for solving continuous space optimization problems. The algorithm is improved with the rapid search capability of AFSA and the good search characteristics of ACO, and the convergence speed of the presented algorithm is also improved for avoiding being trapped in local optimization. The improved algorithm has been tested for varieties of functions. And the algorithm can handle these optimization problems very well.
Keywords
optimisation; stochastic processes; artificial fish-swarm algorithm; improved ant colony algorithm; stochastic optimization algorithm; Ant colony optimization; Cities and towns; Computer applications; Convergence; Euclidean distance; Information science; Space technology; Stochastic processes; Testing; Traveling salesman problems;
fLanguage
English
Publisher
ieee
Conference_Titel
Natural Computation, 2008. ICNC '08. Fourth International Conference on
Conference_Location
Jinan
Print_ISBN
978-0-7695-3304-9
Type
conf
DOI
10.1109/ICNC.2008.75
Filename
4666855
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