Title: Application of a hybrid genetic algorithm based on the travelling salesman problem in rural tourism route planning

Authors: Zhijia Chen; Ping Zhang; Lei Peng

Addresses: School of Business and Trade, Nanjing Vocational University of Industry Technology, Nanjing, Jiangsu Province, 210023, China ' School of Information Management and Engineering, Shanghai University of Finance and Economics, International Education College, Nanjing Vocational University of Industry Technology, Nanjing, Jiangsu Province, 210023, China ' Sol International School, Woosong University, Daejeon, 34606, South Korea

Abstract: It is very meaningful to integrate tourism resources, excavate valuable tourism information and develop a self-service tourism route planning system. In this study, a hybrid genetic algorithm (HGA) based on the travelling salesman problem (TSP) is proposed, and the proposed algorithm is simulated and case-analysed. The research shows that the HGA algorithm has better optimisation efficiency when the number of iterations is less; when there are many urban attractions and large distances, the HGA algorithm will show more cross-routes. After multiple iterations, the optimisation effect and results of the algorithm will be better. There is still much room for improvement in the method proposed in this study. In the next step, map technology can be used to design more detailed route display functions.

Keywords: TSP; travelling salesman problem; genetic algorithm; ant colony rural tourism; route planning.

DOI: 10.1504/IJCSM.2024.136816

International Journal of Computing Science and Mathematics, 2024 Vol.19 No.1, pp.1 - 14

Received: 18 May 2022
Accepted: 27 Feb 2023
Published online: 22 Feb 2024 *