A multi-objective optimization of window surface and glass thickness determination for daylight factor, thermal resistance and acoustic insulation of a test room performances under an overcast sky - Baadache, Khireddine; Guedouh, Marouane Samir; Haddad, Djamel (Journal of Building Engineering, 2025)
This research aims to provide a holistic solution for optimizing window surface Sv area and glazing thickness d in test room under an overcast sky. By focusing on daylighting, thermal resistance, and acoustic insulation, we seek to achieve a balance that enhances overall indoor environmental quality. Utilizing advanced multi-objective optimization techniques (MOGA) in MATLAB, particularly the Pareto optimization approach, this study evaluates the trade-offs among the competing objectives of daylight factor (DFm), thermal resistance (Rth), and acoustic insulation (R). Our findings determine the optimal configuration of window surface (Sv = 5.1074 m2) and glazing thickness (d = 0.0239m) that concurrently improves natural lighting (DFm" of 55.62 %.), thermal insulation (Rth" by 41.25 %), and noise reduction (R″ by 84.53 %). In addition, increasing the glass thickness d is a determined factor that enhance thermal resistance Rth and sound reduction index R. This method offers architects valuable insights into how different parameters affect building design objectives, helping them achieve an optimal window design and glass thickness that enhances daylight performance while improving indoor thermal conditions and acoustic insulation. •Optimizing window surface and glazing thickness in test room under an overcast sky.•Use of Multi-Objective Genetic Algorithm in the building design process.•Glass thickness is a key factor for thermal and acoustic insulation and Daylighting.