Abstract：

Juneau, Alaska, is one of Alaska's most popular tourist destinations. A large influx of cruise tourists each summer brings significant revenue to the local economy. However, overtourism poses numerous challenges, including congestion of infrastructure, retreat of the Mendenhall Glacier, and increased pressure on residents' lives. To address this, a multi-objective optimization model is constructed to achieve sustainable tourism development in Juneau, considering four key dimensions: economic, environmental, social, and cultural. It optimizes key factors like tourist numbers and total revenue to meet diverse objectives. The model employs a solution strategy combining particle swarm optimization (PSO) and the Monte Carlo method. It first optimizes parameters of key indicators to find "balance points" for sub-indicators, then integrates optimal solutions of the four dimensions to calculate a comprehensive score. Sensitivity analysis shows that social and environmental indicators are critical to Juneau's tourism sustainability, particularly resident satisfaction and environmental negatives like carbon emissions. Additionally, allocating extra revenue to conservation efforts is a necessary consideration for sustainable tourism.

Key Words：

sustainable tourism; multi-objective optimization; PSO; Monte Ca