An Optimal Round-Trip Route Planning Method for Tourism Based on Improved Genetic Algorithm

• Published in: Computational intelligence and neuroscience Vol. 2022; pp. 1 - 8
• Main Author: Cao, Sha
• Format: Journal Article
• Language: English
• Published: New York Hindawi 28.08.2022; John Wiley & Sons, Inc
• Subjects: Algorithms; Collaboration; Genetic algorithms; Genetic research; Immunoglobulin A; Methods; Optimization; Path planning; Planning; Route planning; Route selection; Tourism; Travel; Travel industry; Travel time; Traveling salesman problem
• ISSN: 1687-5265; 1687-5273; 1687-5273
• DOI: 10.1155/2022/7665874

The optimization of the travel route for a round-trip is not only a customized demand made by a large number of independently guided tourists but also an essential practical issue for the development of tourism management and tourism businesses. In light of this, the study presents a genetic algorithm (GA) as a potential solution to the problem of how to visit a number of tourist destinations within a constrained area in order to quickly determine the shortest tourist route. To traverse areas or regions with the least amount of physical exertion, select the correct and shortest route. Examining all potential routes from the starting point to the destination will allow you to determine the quickest route. A condensed explanation of the enhanced GA is provided to start. The second step is to analyze the model’s construction and solution in detail. Next, an enhanced genetic algorithm (IGA) is utilized to determine the optimal travel route for visiting a variety of tourist attractions. In accordance with the optimal travel route, the required number of days and specific travel arrangements are then estimated. In conclusion, the GA is optimized, and a simulation examination of each individual’s average path convergence is conducted. The results of the experiments indicate that the IGA can be effectively applied to the path planning of multiple scenic locations, the selection of the shortest travel route, the reduction of travel expenses, and the saving of travel time. This has important implications for both research and practical applications, as well as a high research significance and practical value.