摘要
为提升游客在极高峰期间景区旅游体验、提高景区服务水平,探讨了基于游客异质性,游客对景区内选择景点的偏好不同、景点间路程时间敏感度的不同。以游客收益最大、景点饱和度一致为优化目标,考虑游客效用、游客广义成本等约束条件,建立双目标优化模型,并利用粒子群算法进行线路优度评价。最后,以浙江某景区为例,进行极高峰期间游线优化,结果表明:模型可以在极高峰期间针对游客偏好进行游线设计。同时,景区在极高峰期间应针对不同的游客进行交通设施的供给,以减少景区拥堵,并让游客有更好的游览体验。
To enhance tourists’travel experience and improve service levels during peak seasons in scenic areas,this study explores the heterogeneity of tourists’preferences for selecting attractions with-in the scenic area and their varying sensitivity to travel time between attractions.With the optimization objectives of maximizing tourists’benefits and achieving consistent attraction saturation,a bi-objective optimization model is established,considering constraints such as tourist util-ity and generalized cost.The particle swarm optimization(PSO)algorithm is utilized to evaluate the optimality of the tour routes.Finally,taking a scenic area in Zhejiang as an example,the opti-mization of tour routes during peak seasons is conducted.The results indicate that the model can effectively design tour routes tailored to tourists’preferences during peak seasons.Meanwhile,scenic areas should provide transportation facilities tailored to different types of tourists during peak seasons to reduce congestion and enhance tourists’travel experience.
作者
丁子航
董洁霜
Zihang Ding;Jieshuang Dong(School of Business,University of Shanghai for Science and Technology,Shanghai)
出处
《建模与仿真》
2024年第4期4904-4911,共8页
Modeling and Simulation
关键词
游客收益
景点饱和度
游线优化
Visitor Revenue
Tourist Attraction Saturation
Tour Route Optimization