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  11. Multi-objective Optimization Of Daylighting Performance And Solar Radiation For Building Geometry Using A Hybrid Evolutionary Algorithm

Multi-objective optimization of daylighting performance and solar radiation for building geometry using a hybrid evolutionary algorithm

Shaoyang Lou1, Xiaojun Luo2, Zhonggou Chen1

  • 1Department of Landscape and Architecture, Zhejiang Agriculture and Forestry University, Hangzhou, 311300, China.

Scientific Reports
|July 22, 2025

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View abstract on PubMed

Summary
This summary is machine-generated.

Architectural geometry optimization balances solar radiation and daylighting for improved building energy efficiency and comfort. This study achieved a 26.89% solar performance and 19.85% daylighting enhancement through advanced algorithms.

Area of Science:

  • Building Science
  • Sustainable Architecture
  • Computational Design

Background:

  • Optimizing solar radiation and daylighting is crucial for building energy efficiency and occupant comfort.
  • Architectural geometry significantly influences these environmental factors.
  • Balancing seasonal solar gain and daylight availability presents a complex design challenge.

Purpose of the Study:

  • To optimize building geometry for balanced solar radiation and daylighting performance.
  • To minimize solar radiation variation across seasons while maximizing useful daylight illuminance (UDI).
  • To integrate performance-based design strategies early in the architectural form-finding process.

Main Methods:

  • Parametric modeling using additive and subtractive design algorithms (EvoMass on Grasshopper).
Keywords:
Daylight simulationGeometry optimizationHot summer and cold winter zoneMulti-objective optimization

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  • Application of a multi-objective evolutionary algorithm (Steady-State Island Evolutionary Algorithm - SSIEA).
  • Optimization of building parameters including dimensions, orientation, and mass distribution.

    • Main Results:

    • The optimized design achieved a more balanced solar radiation distribution across seasons.
    • A 26.89% improvement in solar radiation performance was observed compared to the reference building.
    • Daylighting performance was enhanced by 19.85%.

    Conclusions:

    • Leveraging the Pareto front in early design stages offers effective geometry optimization strategies.
    • Performance-based design decisions can be enabled through computational tools.
    • Optimized architectural geometry leads to significant improvements in building energy efficiency and daylighting.
    Solar radiation simulation