Tourism Route Planning of Cultural Heritage Scenic Spots Based on Genetic Simulation Ant Colony Algorithm

Abstract

In recent years, with the development of economy, tourism accounts for an important part of the global economic pattern. The state has gradually rated some scenic spots with a large number of tourists and profound cultural heritage as 5A scenic spots. Since 2007, 279 tourist attractions have been rated as 5A scenic spots in China, including 13 in Henan Province. However, due to the late evaluation of individual scenic spots and the poor local traffic conditions, the number of tourists in scenic spots is small, and the tourism cost and maintenance are relatively high, which has a certain impact on the national economy and local economic level. In order to activate some depressed scenic spots and reduce the economic losses caused by tourism congestion, it is necessary to adjust and plan the tourism route model of 5A scenic spots. Based on the research of famous scholars at home and abroad on the traveling salesman (TSP) problem, this paper establishes the shortest path model that meets the constraints. At the same time, genetic algorithm and ant colony algorithm are used to optimize the scheme respectively to obtain the shortest path programming model that meets the conditions. Finally, each tourism route map and the total tourism distance are given.