旅游景区的准入批量与最大容量分析

The Access Batch and the Maximum Carrying Capacity of Scenic

最近,学者黄羊山在多篇文章中对我国一些标准和规范里的旅游空间容量算法进行了一些探讨,并做出了重要改进。但是,其提出的"取小法"虽然能够保证了游客数不超过景点的容量限制,却没有考虑景点之间距离对容量的影响,且推导过程比较复杂难懂。文章以游客在景区中的移动行为为出发点,将景区旅游线路类比为旅游生产线,利用旅游生产线的平行移动特征,推导出在景区日开放时间内能够准入的游客批数和接待量模型。然后,利用景区内景点游览时间的最大公约数进行景点分解,按照分解后的子景点设置进入批量,从而分别给出了有游览顺序和无游览顺序的旅游高峰期的最大容量计算模型。最后实例计算表明,该方法确实可以在旅游高峰期尽量减少景点闲置提高接待量。

During the peak tourism season the number of tourists allowed access at any one time and the maximum carrying capacity of scenic areas should be sufficient to fully exploit the layout of the area. The number of tourists visiting the scenic location should be controlled so as not to exceed the capacity of each individual attraction in the location. Huang previously investigated the carrying capacity of scenic areas. He presented improvements on the traditional model for calculating the ca,Tying capacity. His model, known as ＂including small elements＂, includes many distinct conditions in its calculations. However, it does not account for the distance between individualattractions, so the carrying capacity of the scenic area calculated from his model is smaller than the reality. Hence, by viewing tourism as a production line, we construct a new scenic capacity calculation model both making full use of the area layout, and ensuring that the number of tourists does not exceed the design capacity of the individual attractions. First, from analysis of tourist behavior in scenic areas, we portray the scenic area tourism route as a production line. The tourists are taken to be the individual product pieces; the scenic spot represents the processes. The movement of tourists along the tourism production line represents the linear movement of the product pieces. Hence, we use production and operations theory to construct a general model to calculate the optimum number of tourists to be allowed access at any one time, and the carrying capacity, of a scenic area during its opening hours. Our general model is the same as Huang＇ s ＂including small elements＂ model. The general model does not account for the time taken to travel between attractions in scenic areas, so the carrying capacity estimated from this model is low. To improve the model, the concept of the virtual sub - attraction is introduced. The scenic area attractions are divided into several virtual sub-attractions, each being assigned the same visit length which was calculated by the greatest common divisor of visit times per attraction. Batch access numbers are set as the carrying capacity of the sub attraction. The impact that the order in which tourists visit the attractions has on the carrying capacity of the scenic area is also analyzed. Two models are constructed： the maximum carrying capacity of the scenic area including visit order, and the maximum carrying capacity of the scenic area excluding visit order. Finally, we undertake empirical analysis. The results show that increasing the size of access batches does not lead to a greater carrying capacity of the scenic area. This is due to the fact that large volumes of tourists can lead to longer waiting times for a long visit time attraction than for a short visit time attraction, and thus makes some of the attractions idle. Our model can increase the number of tourists by minimizing the down-time of attractions in scenic areas during the peak tourism season.