A Tourist Itinerary Planning Approach Based on Ant Colony Algorithm

Abstract

Many itinerary planning applications have been developed to assist travelers making decisions. Existing approaches model this problem as finding the shortest path of tourism resources and generate either inter-city or intra-city visiting plans. Instead of following the conventional route, we propose an approach to automatically generate tourist itineraries by comprehensively considering transportations, lodgings and POIs between/inside each destination. In addition, due to the NP-complete nature of the itinerary planning, we develop an approach based on the ant colony optimization (ACO) algorithm to solve the tourist planning problem. To show the versatility of the proposed approach, we design an itinerary planning system which arranges all available tourism resources collected from the web, such as POIs, hotels, and transportations. Our experimental result confirms that the proposed algorithm generates high utility itineraries with both effectiveness and efficiency.