Study on Improved Ant Colony Algorithm in Dynamic Multi-Paths Route Guidance System


Article Preview

The traditional Dynamic Route Guidance System (DRGS) provides only the optimal path to the travelers, which may easily lead to aggregative response of the travelers and overcrowding drift. This paper presents an approach based on Ant Colony Optimization (ACO) for solving the k-shortest paths problem in DRGS. In order to improve the convergence rate, the basic ACO is improved by introducing direction function the weight coefficient of which can be adjusted to vary state transition rule and standardized transformation to eliminate the influence of the size and dimension of pheromone and heuristic information. Compared with basic ACO, simulation experiments indicate that the improved ACO is more effective and efficient.



Edited by:

Qi Luo




J. H. Gu et al., "Study on Improved Ant Colony Algorithm in Dynamic Multi-Paths Route Guidance System", Applied Mechanics and Materials, Vols. 20-23, pp. 243-248, 2010

Online since:

January 2010




[1] Park D. Multiple Path based vehicle routing in dynamic and stochastic transportation networks: [dissertation]. Texas A&M University, (1998).

[2] Su Yongyun, Yan Kefei, Yang Xiaoguang, et al. Study of the algorithm of dynamic travel time and multi-end shortest path in VNS. China Journal of Highway, 2001, 14(1): 97-103.

[3] Yang Qun, Guan Wei, Zhang Guowu. Study on Multi-path Based Route Choice Approach. Journal of Industrial Engineering and Engineering Management, 2002(4): 42-45.

[4] Li Chunyuan. Study on the Multi-path Guidance Strategy of Dynamic Route Guidance System. MA Dissertation, Changsha University of Science &Technology, 2008, 10-13.

[5] Li Shiyong. Ant colony algorithms with applications. Harbin: Harbin Institute of Technology Press, (2004).

[6] M Dorigo, V Maniezzo, A Colorni. Positive Feedback as a Search Strategy. Technical Report 91-016.

[7] Zhang Meiyu, Huang Han, Hao Zhifeng, et al. Path Planning for Robots Based on Ant Colony Algorithm. Computer Engineering and Applications, 2005, 41(25): 34-37.