American Journal of Information Science and Computer Engineering
Articles Information
American Journal of Information Science and Computer Engineering, Vol.5, No.2, Jun. 2019, Pub. Date: May 28, 2019
Ant Colony Algorithm for Travel Route Planning
Pages: 66-71 Views: 250 Downloads: 102
Authors
[01] Xiaoyang Zheng, Institute of Liangjiang Artificial Intelligence, Chongqing University of Technology, Chongqing, China.
[02] Fengsi Yu, College of Science, Chongqing University of Technology, Chongqing, China.
[03] Guyue Tian, College of Science, Chongqing University of Technology, Chongqing, China.
[04] Liqiong Qiu, College of Science, Chongqing University of Technology, Chongqing, China.
Abstract
The developments of society and the living standards have greatly facilitated people's travel. Thus, how to choose a tourism strategy becomes an important problem in many tourist routes. Aiming at the tourist route optimization problem of nine cities in China, this paper first collects the track mileage and the actual high-speed train or train fares between every two cities. Second, the optimal distance and cost of the travel are solved by the ant colony algorithm (ACA) based on the datum collected, respectively. Finally, travel evaluation index of combination the travel time with the fare are computed. Then the values of the travel index matrix are regarded as the weights in the weighed graph of the traveling salesman problem. Similarly, the ACA is implemented to solve the optimal tourism route with travel time and fare. On the whole, reasonable and optimal travel route and booking schemes are proposed for this practical tourism problem and provided for the traveler to choose a suitable travel route.
Keywords
Ant Colony Algorithm, Shortest Distance, Least Cost, Travel Evaluation Index
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