Multi-Objective Trip Planning Based on Ant Colony Optimization Utilizing Trip Records

Etsushi Saeki*, Siya Bao, Toshinori Takayama, Nozomu Togawa


研究成果: Article査読

5 被引用数 (Scopus)


Trip planning services have been developed along with tourism promotion and information technology evolutions, where we must construct trip routes that simultaneously optimize multi-objective functions such as trip expenses and user satisfaction. Moreover, utilization of past-trip records is essential, because similarities to past-trip records well reflect users' general preferences and tendencies during trip planning. In this paper, we propose a multi-objective trip planning method using ant colony optimization (ACO). By effectively using the pheromones in ACO, we can construct trip routes similar to trip records stored before and the constructed route can reflect users' general preferences. In addition, we vary ants' behaviors in ACO corresponding to various objective functions and hence we can obtain multi-objective trip routes naturally. Experimental results demonstrated that our method outperforms the baseline methods in terms of point-of-interest (POI) satisfaction, POI cost, and past-trip similarity. We also conducted a user study, which clearly indicates that our method obtains high scores through various user questionnaires.

ジャーナルIEEE Access
出版ステータスPublished - 2022

ASJC Scopus subject areas

  • コンピュータサイエンス一般
  • 材料科学一般
  • 工学一般
  • 電子工学および電気工学


「Multi-Objective Trip Planning Based on Ant Colony Optimization Utilizing Trip Records」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。