TY - GEN
T1 - A tourist itinerary planning approach based on ant colony algorithm
AU - Yang, Lei
AU - Zhang, Richong
AU - Sun, Hailong
AU - Guo, Xiaohui
AU - Huai, Jinpeng
PY - 2012
Y1 - 2012
N2 - 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.
AB - 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.
KW - ant colony algorithm
KW - itinerary planning
KW - tourist guide
UR - https://www.scopus.com/pages/publications/84865635970
U2 - 10.1007/978-3-642-32281-5_39
DO - 10.1007/978-3-642-32281-5_39
M3 - 会议稿件
AN - SCOPUS:84865635970
SN - 9783642322808
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 399
EP - 404
BT - Web-Age Information Management - 13th International Conference, WAIM 2012, Proceedings
T2 - 13th International Conference on Web-Age Information Management, WAIM 2012
Y2 - 18 August 2012 through 20 August 2012
ER -