Building Sustainable Tourism Based on Genetic Algorithm Optimization of Partial Least Squares Method

This study proposes a sustainable tourism optimization model by integrating Partial Least Squares Regression (PLSR) and Genetic Algorithms (GA). Targeting over-tourism issues in cities like Juneau and New York, the model balances economic growth, environmental protection, and social well-being. PLSR identifies key influencing factors such as income, crime rates, and emissions, while GA optimizes policy variables to achieve multi-objective goals. Results show strong explanatory power (R² > 0.9) and offer practical, data-driven strategies for sustainable urban tourism development.