Author(s)

Anqi Leng, Xueqing Bai, Xinyu Jiang, Liyuan Zheng, Xiaoran Wang, Wanjing Zhang

Corresponding Author

Anqi Leng

Abstract

Rising living standards and global mobility have increased tourism demand, often causing overtourism, environmental degradation, resource pressure, and social disruption, which threaten community well-being and destination competitiveness. Achieving sustainable tourism requires balancing economic, environmental, and social objectives. This study develops a Sustainable Tourism Management Model based on System Dynamics and Multi-Objective Optimization to address these challenges. Tax allocation ratios serve as control variables, while Particle Swarm Optimization (PSO) and NSGA-II are applied to identify Pareto optimal solutions, enabling effective management of tourist flows, infrastructure, and community development. Case studies demonstrate the model’s capability to guide policy, mitigate environmental pressure, and optimize resource allocation. The framework can be extended to other multi-objective domains, such as urban planning and regional resource management, and its adaptability is enhanced through field-specific indicators, real-time data, and intelligent forecasting. By combining methodological rigor with dynamic optimization, the model provides a practical tool for policymakers and planners to manage overtourism and promote sustainable tourism across diverse regions.

Keywords

Overtourism; System dynamics; Multi-objective optimization; PSO; NSGA-II; Tourist flow balance