Academic Journal of Computing & Information Science, 2024, 7(12); doi: 10.25236/AJCIS.2024.071203.
Qing Liu, Xudong Zhan
School of Electronic and Information Engineering, Liaoning Technical University, Huludao, 125100, China
This study focuses on the planning of travel routes for foreign tourists in China, aiming to maximize the weighted sum of the number of tourist attractions and their ratings while minimizing the total cost. For this purpose, this paper selects "the 50 most desirable cities for foreign tourists" from 352 cities in China as the research object. The dynamic programming algorithm is adopted, and various constraint conditions such as starting the tour at a designated location and ending the journey within a specified time are considered to formulate travel routes. In addition, for tourists who prefer visiting attractions of specific types, this study also collects the latitude and longitude information of 352 cities in China, constructs a graph model, and designs a heuristic function and uses the A* algorithm for heuristic search. Eventually, an effectively implementable travel route is planned.
Tourism Route Planning, Dynamic Programming Algorithm, Heuristic Search, Specific Types of Tourist Attraction
Qing Liu, Xudong Zhan. Research on Domestic Tourism Route Planning Based on Dynamic Programming and Heuristic Search. Academic Journal of Computing & Information Science (2024), Vol. 7, Issue 12: 16-23. https://doi.org/10.25236/AJCIS.2024.071203.
[1] Shan Xinghua, Zhao Shuo. High-speed rail passenger flow distribution method considering travel preferences of passenger groups [J]. Railway Computer Application, 2024, 33(08): 12-18.
[2] Tang Kezong, Liu Kang, Liu Yujiao. Tourism route planning of Jingdezhen ceramic culture scenic area based on weight disturbance mechanism simulated annealing genetic algorithm[J]. Software Guide, 2023, 22(04): 96-102.
[3] Zhang Ruijiao, Chen Chongcheng, Huang Zhengrui, et al. Solving cultural tourism route planning problems with improved genetic algorithm[J]. Journal of Guizhou University (Natural Sciences Edition), 2022, 39(01): 57-64.
[4] Gong Yuhuang. A study on artificial intelligence-based travel route recommendation system trust and willingness to accept [D]. Southwestern University of Finance and Economics, 2021.
[5] Song Y , Ding D , Wang R ,et al.Analysis and Design of the Shopping Trolley for Elderly People Based on Ergonomics[J].Springer, Singapore, 2023.DOI:10.1007/978-981-19-4786-5_31.
[6] Li Min, Zhu Nan, Li Minghui. A study on Chengdu inner-city travel route planning based on SA and GA algorithm [J]. Value engineering, 2022, 41(28): 38-40.
[7] Wong Chi Ho. Path planning and trajectory optimization based on improved A-star algorithm [D]. Jilin University, 2024.
[8] Wei Xin. Research on personalized travel route generation modeling based on user interest model [J]. Automation technology and applications, 2024, 43(03): 177-180.
[9] Liu Na. Method of route recommendation based on preference data [J]. Information Technology, 2023, (11): 148-152 + 157.
[10] Li Xia, Yin Chuandong, Yuan Yun. Comparative Analysis of travel route personalized recommendation algorithms [J]. Computer Technology and development, 26(09)2016:73-77.