Research on daylighting optimization of building space layout based on parametric design

Abstract

Excellent daylighting in buildings is beneficial to protect the physical and mental health of users. After introducing the daylighting of the building, this paper used the genetic algorithm (GA) optimized by co-evolution to optimize the daylighting. Then, a one-story L-shaped accommodation house in Zhengzhou, Henan Province was taken as a case for analysis. The effectiveness of the Daysim software used for calculating the building lighting indicator was tested. Then, the performance of the improved GA with different daylighting indicators as fitness values was compared. Finally, the optimization performance of the particle swarm optimization (PSO) algorithm, the traditional GA, and the improved GA were compared. The results showed that the daylighting indicators simulated by Daysim were significantly correlated with the measured data, suggesting its effectiveness. The improved GA using dynamic daylighting indicators as fitness values had better optimization performance. Compared with the other two algortihms, the improved GA had better optimization performance.