A Study on Sustainable Tourism Optimization Based on a Logistic-Driven RTS Model

As one of the fastest-growing industries in the world, tourism has become an important driver of economic development. However, its rapid expansion has also brought about serious environmental degradation and social unrest, especially in regions facing overtourism. Therefore, sustainable tourism has become a global priority. This study proposes an RTS tourism optimization model to balance economic benefits, environmental impacts, and social well-being. The three optimization factors of the model are total tourism revenue (R), tourism carbon footprint (TCF), and social happiness index (SH), which represent the economic, environmental, and social dimensions, respectively. The economic revenue (R) is modeled using a logistic model to simulate the initial growth and subsequent saturation stages of tourism development, thereby obtaining the RTS optimization model. The model is applied to overtourism cities (Juneau). The Pareto optimal solution is selected based on the entropy weight method (EWM) using the NSGA-II and NSGA-III algorithms combined with actual data. The results show that the proposed model can significantly reduce the environmental burden and improve the well-being of residents while ensuring an acceptable level of tourism revenue, which provides a flexible and scalable framework for local governments to design evidence-based sustainable tourism development policies.