An Adaptive Ant Colony Algorithm Improved and Simulation

Abstract:

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Ant colony algorithm is a new evolutionary algorithm, Ant colony algorithm is widely used to solve combinatorial optimization problems, But the ant colony algorithm has slow convergence speed and prone to stagnation phenomenon. This paper presents an evolution strategy based on adaptive selection and dynamic adjustment to improve ant colony algorithm, the simulation results show that the algorithm performance significantly improved, this method can not only accelerate convergence rate, and save search time, but also can overcome premature stagnation of behavior, and to find a better solution. This is very favorable for solving large-scale optimization problem.

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Periodical:

Edited by:

Ford Lumban Gaol, Mehdi Roopaei, Svetlana Perry and Jessica Xu

Pages:

209-212

DOI:

10.4028/www.scientific.net/AMM.87.209

Citation:

Y. S. He and X. Li, "An Adaptive Ant Colony Algorithm Improved and Simulation", Applied Mechanics and Materials, Vol. 87, pp. 209-212, 2011

Online since:

August 2011

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Price:

$35.00

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