Multi-objective Optimization of Classroom Window Design for Energy and Thermal Comfort in Hot-Humid Climates

School buildings in hot-humid climates face significant challenges in balancing energy efficiency and thermal comfort due to this environment, necessitating optimized design strategies to reduce energy consumption while enhancing occupant comfort.This study introduces a multi-objective optimization framework for window design in school buildings situated in hot-humid climates, targeting a balance between Energy Use Intensity (EUI) and Thermal Comfort Time Ratio (TCTR). Exploring multi-objective optimization through NSGA-II genetic algorithms, conducts Sobol sensitivity analysis for parameter assessment, and employs Gaussian Process Regression（GPR） for effective model validation, the research identifies optimal window configurations that reduce energy consumption while enhancing thermal comfort. It finds that the Window-to-Wall Ratio (WWR) and Solar Heat Gain Coefficient (SHGC) are the most significant factors, with WWR and SHGC accounting for 28.1% and 23.7% of the variance in EUI and TCTR, respectively. The results reveal a non-linear trade-off between the objectives, with the Balanced Solution providing a practical compromise of a 6.7% reduction in energy use and a 14.3% increase in thermal comfort. The GPR model exhibited high predictive accuracy, with R² values of 0.91 for EUI and 0.95 for TCTR, underscoring the framework's effectiveness. This research offers actionable insights for designing energy-efficient and comfortable school buildings in hot-humid climates, enriching sustainable architectural design knowledge.