This paper studies how to obtain a reasonable traveling route among given attractions. Toward this purpose, we propose an objective optimization model of routes choosing, which is based on the improved Ant Colony Algorithm. Furthermore, we make some adjustment in parameters in order to improve the precision of this algorithm. For example, the inspired factor has been changed to get better results. Also, the ways of searching have been adjusted so that the traveling routes will be well designed to achieve optimal effects. At last, we select a series of attractions in Beijing as data to do an experimental analysis, which comes out with an optimum route arrangement for the travelers; that is to say, the models we propose and the algorithm we improved are reasonable and effective.
 T. Stutzle and H. Hoos, “Max-Min Ant System and Local Search for the Travelling Salesman Problem,” IEEE International Conference on Evolutionary Computation and Evolutionary Programming Conference, 1997, pp. 309-314.
 T. Stuezle and M. Dorigo, “A Short Convergence Proof for a Class of Ant Colony Optimization Algorithms,” IEEE Transactions on Evolutionary Computation, Vol. 6, No. 4, 2002, pp. 358-365. http://dx.doi.org/10.1109/TEVC.2002.802444
 M. Dorigo and L. M. Gambardella, “Ant Colonies for the Travelling Salesman Problem,” BioSystems, Vol. 43, No. 2, 1997, pp. 73-81. http://dx.doi.org/10.1016/S0303-2647(97)01708-5
 W. J. Gutjahr, “A Graph-Based Ant System and Its Convergence,” Future Generation Computer System, Vol. 16, No. 8, 2000, pp. 873-888. http://dx.doi.org/10.1016/S0167-739X(00)00044-3
 J. H. Yoo, R. J. La and A. M. Makowski, “Convergence of Ant Routing Algorithms—Results for Simple Parallel Network and Perspectives,” Technical Report CSHCN 2003-44, Institute for Systems Research, University of Maryland, College Park (MD), 2003.
 L.Y. Li and Y. Xiang, “Research of Multi-Path Touting Protocol Based on Parallel Ant Colony Algorithm Optimization in Mobile Ad Hoc Networds,” 5th International Conference on Information Technology: New Generations, 2008.