An Improved Ant Colony Algorithm Based on Path Optimization Strategy for TSP

Ben Can Gong; Ting Yao Jiang; Shou Zhi Xu; Peng Chen

doi:10.4028/www.scientific.net/AMM.543-547.1681

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 543-547An Improved Ant Colony Algorithm Based on Path...

An Improved Ant Colony Algorithm Based on Path Optimization Strategy for TSP

Abstract:

Traveling salesman problem (TSP) is not only a combinatorial optimization problem but also a classical NP-hard problem, which has high application value. Ant colony algorithm (ACA) is very effective for solving TSP problem, but basic ant colony algorithm has drawbacks of low convergence rate and easily trapping in local optimal solution. An improved ant colony algorithm was proposed. It used path optimization strategy to exchange the position of cities to find the better solution for TSP. Simulation results show the improved algorithm has better optimal solution and higher efficiency.

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Periodical:

Applied Mechanics and Materials (Volumes 543-547)

Pages:

1681-1684

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.543-547.1681

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Online since:

March 2014

Authors:

Ben Can Gong*, Ting Yao Jiang, Shou Zhi Xu, Peng Chen

Keywords:

Ant Colony Algorithm, Path Optimization Strategy, TSP

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