Synergistic Equilibrium
Optimizing tourism vs. environment with 8.3% prediction error
8.3% prediction error
8.3%
Prediction Error
28K+
Teams Globally
R²>0.5
Model Fit
3
Objectives Balanced
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Tourism and environmental sustainability are a zero-sum game—or so the standard models assume. MCM/ICM 2025 (Problem B) challenged us to find synergies. We built a three-dimensional coupled model linking tourist flow, environmental quality, and social satisfaction through system dynamics, then optimized with NSGA-III to find the Pareto frontier.
Achieved 8.3% tourist prediction error with R²>0.5 on the coupled model. PCA-KMeans clustering identified distinct destination archetypes with different optimal strategies. Competed against 28,000+ teams globally—Honorable Mention.
Python
NSGA-III
System Dynamics
Analytics
NSGA-IIISystem DynamicsPCA-KMeans