With the advancements and developments in China’s tourism industry, various autonomous forms of tourism have been gaining prominence. As such, to facilitate tourists and provide them with maximum experience while economizing on time and cost is essential. One approach toward achieving this is the optimization of tourism routes. However, so far the studies on this approach have focused primarily on inland tourist sites and have lacked a geographic perspective. Therefore, this study undertook the tourism resource data of Lushunkou District of 2020, used the ArcGIS accessibility evaluation model to analyze tourism resources, and finally used the Vehicle Routing Problem of network analysis technology to optimize the tourism route of Lushunkou District and obtain the general overall intellectual framework and technical methods for tourism route optimization. The results showed that the ArcGIS accessibility evaluation model could be used to integrate resources in the tourism area before using the Vehicle Routing Problem to optimize the analysis of tourism routes, thereby enabling the separation of different types of tourism. These divisions were based on the Vehicle Routing Problem to optimize routes for one-day and two-day tours. A new method and model for optimization for tourism routes was constructed to provide a basis and reference for the optimization of tourism routes in similar cities. The observations and results of the present study can facilitate the government in developing the tourism industry and maximizing the benefits obtained from them. Further, travel agencies and tourists will have the provision of designing optimum tourism routes.

In recent years, the rapid improvement in the urbanization level of the Central Plains urban agglomeration is bound to bring about significant changes in urban land expansion and economic development. However, at present, there is little attention paid to the research on the spatiotemporal interaction characteristics of urban expansion and the interaction between urban expansion and economic development in this region, and existing research lacks a geographical analysis perspective. This study uses spatial autocorrelation, hot spot analysis, LISA time path, and standard deviation ellipse models to analyze the spatiotemporal interaction characteristics of urban expansion in the Central Plains urban agglomeration from 1990 to 2020, and it uses bilateral spatial autocorrelation and decoupling models to analyze the spatial correlation and decoupling effects of urban expansion and economic development. The results show that (1) the urban built-up area of the Central Plains urban agglomeration as a whole is growing in a “J” shape, and the expansion rate has increased rapidly in the past 10 years. (2) The spatial expansion of the city is mainly in the direction of “northwest–southeast”; the directionality has been gradually strengthened in the past 10 years, mainly in the direction of several prefecture-level cities under the jurisdiction of Anhui Province, and the spatial center of gravity of the city has shifted significantly to the south. (3) The spatial agglomeration characteristics of urban expansion in the Central Plains urban agglomeration are not obvious; local hot spots are concentrated in Jiaozuo and its surrounding areas, and urban expansion has local spatial structural instability. (4) During the 2005–2020 period, the risk of uncoordinated urban expansion and economic growth in the Central Plains urban agglomeration increased. This study is of great significance for the rational control of regional development, providing empirical reference for the formulation of the development planning of the Central Plains urban agglomeration, as well as providing a reference for research ideas and methods related to urbanization.