Tourism combination forecasting with swarm intelligence - Li, Hengyun; Guo, Honggang; Wang, Jianzhou; Wang, Yong; Wu, Chunying (Annals of tourism research, 2025)
Combination forecasting is an effective method for improving the accuracy of tourism demand. This study proposes an innovative combination strategy based on a multi-objective swarm intelligence optimization algorithm and, for the first time, examines whether and how this algorithm can enhance the performance of tourism demand combination forecasting. An empirical study conducted under several scenarios demonstrates that the proposed combination strategy enhances the interaction among single forecasts, leading to improved forecast accuracy and stability compared with traditional combination methods. The model remained effective even during the COVID-19 pandemic. The findings have a positive impact on predictive research, offering new insights and methodologies for tourism demand modeling. •This study forecasts daily and weekly tourism demand for three tourism destinations.•A novel combination method based on multi-objective swarm intelligence is proposed.•The proposed method can enhance both forecast accuracy and stability.•The proposed method can improve forecast accuracy even in turbulent period.