Tourist route planning is a challenging task that requires considering both temporal and spatial dimensions of tourism data. On one hand, it involves obtaining the spatial distribution of tourist attractions within the scenic area, and on the other hand, it takes into account the tourists' visiting behaviors during their exploration of the area. Therefore, in addition to collecting attribute information of various attractions in the scenic area, tourism route planning also requires a significant amount of data on tourists' visiting behaviors. This paper collects the aforementioned data and extracts the travel behavior information of tourists between attractions, proposing important indicators for measuring tourist travel behavior. Based on a comprehensive consideration of these indicators, the Travel Route Planning algorithm (TRP) is introduced with the aim of significantly reducing travel time between attractions. The experiments yield distinct results and corresponding travel times between scenarios without travel route planning and scenarios with travel route planning. Furthermore, by further optimizing the route planning, a comparison of travel times before and after optimization is obtained. The results indicate that the Travel Route Planning algorithm not only greatly reduces travel time but also provides valuable insights for determining optimal locations for tourist buses to make stops. Compared to three representative path planning algorithms currently available, the algorithm proposed in this paper exhibits significant advantages in response time and average solution quality.
WANG Feng
,
HANG Bo
,
HUANG Jinzhou
,
XU Degang
,
ZHANG Zeyu
,
LIU Jiamou
. Research of touring route planning based on spatio-temporal awareness[J]. Operations Research Transactions, 2026
, 30(2)
: 69
-78
.
DOI: 10.15960/j.cnki.issn.1007-6093.2026.02.005
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