Tourism Route Planning Based on 0-1 Algorithm and Multi-Traveler Modeling--A Case Study of Sichuan Province

DOI

10.2991/978-94-6463-570-6_24How to use a DOI?

Keywords

TSP model; Multi-traveler problem; 0-1 planning; Minimum spanning tree method; Route planning

Abstract

With the booming development of tourism market, how to efficiently plan tourism routes has become a common concern of travelers and tourism departments. In this paper, the TSP model and multi-traveler model for tourism route planning are established for the Sichuan tourism problem by using mathematical modeling techniques such as 0-1 planning and minimum spanning tree method, combined with equilibrium function. By studying the approximate optimal solution of the NP-hard problem, it provides tourists with an economical and efficient tourism route planning scheme. The research results show that the model proposed in this paper can effectively solve the tourism route planning problem and provide decision support for tourists and tourism departments.

Copyright

© 2024 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Kaifeng Xu
AU  - Qianqian Bai
AU  - Junhao Ke
AU  - Yanshuo Zhang
AU  - Jiaxin Ying
PY  - 2024
DA  - 2024/11/22
TI  - Tourism Route Planning Based on 0-1 Algorithm and Multi-Traveler Modeling--A Case Study of Sichuan Province
BT  - Proceedings of the 2024 5th International Conference on Management Science and Engineering Management (ICMSEM 2024)
PB  - Atlantis Press
SP  - 221
EP  - 226
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6463-570-6_24
DO  - 10.2991/978-94-6463-570-6_24
ID  - Xu2024
ER  -