Research on Sustainable Development of Tourism Industry in Juneau Based on Nonlinear Optimization

Abstract

This study constructs a comprehensive mathematical model to assess the current state of tourism development in Juneau and propose sustainable optimization strategies. The model integrates key factors such as visitor numbers, carbon emissions, infrastructure pressure, and resident satisfaction. Aiming to maximize economic benefits and minimize environmental and social costs, it incorporates a feedback mechanism to characterize the dynamic redistribution of tourism revenue across infrastructure, environmental protection, and community welfare investments. Sensitivity analysis verifies the robustness of the model. The model is further extended to overtourism cities such as Xi'an. Using the analytic hierarchy process (AHP) to identify core influencing factors, a strategy for attracting less popular attractions based on dynamic pricing, facility improvements, and transportation optimization is proposed. Finally, multi-objective coordinated optimization is achieved by adjusting weights and pricing parameters. Prediction results indicate that this strategy can increase tourism revenue by approximately 20% while reducing carbon emissions by approximately 15%, providing a quantifiable and scalable decision-making framework for addressing overtourism and achieving sustainable urban tourism development.