Path Optimization Model of Rural Red Tourist Attractions Based on Ant Colony Algorithm

As an important historical and cultural heritage, rural red tourism sites have high historical, cultural, and social values. Moreover, rural red tourism sites are suitable for development and protection as tourism resources due to their unique landscape, architecture, culture, and art. In this paper, we propose a path generation model based on an ant colony algorithm to recommend the best path for tourists to visit rural red tourism sites. First, this paper investigates the modeling methods of path planning and multiobjective planning and their related solution algorithms to prepare for the establishment and solution of the tour path generation model for rural red tourism sites. By analyzing the problem description, this paper proposes the two model objectives of the shortest tour path and the highest total rating of the tourist attraction, and the model limitation of the total tour usage time, to model the model with a multiobjective planning approach. Then, by modifying the calculation of visibility and pheromone increments of the ant colony algorithm, the modified ant colony algorithm can take into account the two objectives of shortest path and highest total rating when constructing the path. Finally, this paper proposes to update the optimal path by using the number of ratings per unit path length as the update criterion of the optimal path.