Optimizing Sustainable Tourism: A Multi-Objective Approach

Abstract

This study develops a comprehensive multi-objective optimization (MOO) framework to address the complex challenge of sustainable tourism management in Juneau, Alaska. By employing advanced genetic algorithms, particularly the NSGA-II approach, the research simultaneously optimizes two competing objectives: maximizing tourism revenue while minimizing negative impacts on infrastructure, environment, and local communities. The model incorporates real-world constraints including waste generation limits, water demand thresholds, CO2 emission caps, and policy adjustment boundaries derived from Juneau's specific conditions. Through the generation of a Pareto-optimal frontier, the study reveals inherent trade-offs between economic development and sustainability goals, providing policymakers with actionable insights. Results demonstrate that optimal tourist numbers and tax adjustments can enhance sustainability without exceeding carrying capacities. The robustness of the proposed approach is validated through sensitivity analysis, establishing its effectiveness in complex, real-world tourism planning scenarios where multiple competing objectives must be reconciled.