Improved Ant Colony Optimization and Application on TSP

Zhi Qiang Fu; Lei An Liu

doi:10.4028/www.scientific.net/AMM.182-183.2055

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 182-183Improved Ant Colony Optimization and Application...

Improved Ant Colony Optimization and Application on TSP

Abstract:

Ant Colony Optimization is an intelligent optimization algorithm from the observations of ant colonies foraging behavior. However, ACO usually cost more searching time and get into early stagnation during convergence Process. We design the improved ant colony algorithm using perturbation method to avoid early stagnation, adjusting volatilization coefficient to increase the exploration of tours at first phase and searching speed at second phase, using hortation method to improved searching efficiency. We apply the improved algorithm on traveling salesman problem showing that the improved algorithm finds the best values more quickly and more stability than Max-Min Ant System algorithm.

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Periodical:

Applied Mechanics and Materials (Volumes 182-183)

Pages:

2055-2058

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.182-183.2055

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Online since:

June 2012

Authors:

Zhi Qiang Fu, Lei An Liu

Keywords:

Ant Colony Optimization (ACO), Perturbation Method, Pheromone, TSP

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