An Enhanced NSGA-II Algorithm with Parameter Categorization for Computational-Efficient Multi-Objective Optimization of Active Glass Curtain Wall Shading Systems

Dezhao Tang and Zhiyong Wang ()
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Dezhao Tang: School of Civil Engineering, Hunan University of Technology, Zhuzhou 412007, China
Zhiyong Wang: School of Civil Engineering, Hunan University of Technology, Zhuzhou 412007, China

Energies, 2025, vol. 18, issue 7, 1-16

Abstract: To address the limitations of the Non-Dominated Sorting Genetic Algorithm (NSGA-II) in optimizing active glass curtain wall shading systems—particularly its suboptimal convergence efficiency and high computational demands—this study proposes an improved NSGA-II algorithm incorporating parameter categorization. Shading system parameters (e.g., slat width, angle, separation, and blind-to-glass distance) are classified into distinct categories based on their character and optimized sequentially. This phased approach reduces the search space dimensionality, lowering computational complexity while maintaining optimization accuracy. The framework integrates user preferences and climatic adaptability to balance energy efficiency and glare mitigation. The louver parameters were optimized under the same experimental conditions, and the enhanced algorithm exhibits 49% lower energy consumption values and 5% smaller visual discomfort time duration compared to the baseline algorithm in the optimization outcomes.

Keywords: glass curtain wall; sunshade louvers; glare; building energy efficiency; multi-objective optimization (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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