Study on Traveling Salesman Problem Based on the Improved Chaos Ant Colony Algorithm

Abstract:

In this paper an improved chaos ant colony algorithm based on return optimization strategy, elite strategy and intersection removal strategy is proposed. The improved algorithm uses orthogonal method to cluster the target points, then adopt chaos technology to optimize initial solution of the ant colony to improve individual quality and chaos perturbation is utilized to avoid the search being trapped into local optimum solutions. The simulation results show that the improved algorithm has higher efficiency in finding optimal path and it is a novel method to solve traveling salesmen problem.

• Periodical: Advanced Materials Research (Volumes 989-994)
• Pages: 2196-2199
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.989-994.2196
• Online since: July 2014
• Authors: Hai Yang*
• Keywords: Ant Colony Algorithm, Chaos Optimization, Simulation Experiment, Traveling Salesman Problem

References

[1] T. Stutzle, H. Hoos. The MAX-MIN ant system and local search for the traveling salesman problern[C]. IEEE Press, 1997, 308-313.

DOI: 10.1109/icec.1997.592327

[2] Marco Dorigo. Ant colonies for the traveling salesman problem [J]. Biosystems, 1997, 43: 73-81.

DOI: 10.1016/s0303-2647(97)01708-5

[3] Kuo, R.J., Wang, H.S., Hu T., Chou, S.H. Application of Ant K-Means on Clustering Analysis. Computers and Mathematics with Applications, 2005, 1709-1724.

DOI: 10.1016/j.camwa.2005.05.009

[4] Wang Yunwu. Application of Chaos Ant Colony Algorithm in Web Service composition based on QoS. International Forum on Information Technology and Applications, 2009. 172: 225-227.

DOI: 10.1109/ifita.2009.172

[5] Wei Gong, Shoubin Wang. Chaos Ant Colony Optimization and Application. Fouth International Conference on Internet Computing for Science and Engineering, 2009. 38: 301-303.

DOI: 10.1109/icicse.2009.38