An Integrated Framework for Multi-Objective Optimization of Night Lighting in Urban Residential Areas: Synergistic Control of Outdoor Activity Places Lighting and Indoor Light Trespass

Abstract

In the context of increasing urban night lighting, the phenomenon of light trespass in residential areas is becoming increasingly serious, affecting the night comfort and circadian rhythm of residents. Aiming at this problem, this paper takes the night lighting of activity places in old multi-story residential areas of Shijingshan, Beijing, as the research object, and proposes a research framework integrating parametric modeling, multi-objective optimization, correlation analysis, and scheme decision-making, aiming to trade off the two objectives of maximizing the night lighting of the activity places and minimizing indoor light intrusiveness. The study first establishes a parametric model based on Rhino and Grasshopper, combines the NSGA-II algorithm with multi-objective optimization simulation to obtain the Pareto optimal solution, analyzes the correlation between the design variables and the objective function by the Spearman method, and finally assists in the scheme decision-making by K-means clustering. The results showed that the streetlight heights (SH), distance between buildings and streetlights (DBS), and streetlight matrix types (SMT) were the key factors affecting lighting performance, which should be emphasized in the actual lighting design. Secondly, the Cluster2 solution set optimally performs the two objective functions. The 18th individual of Generation 15 (Gen. 15 Ind. 18) and Gen. 31 Ind. 42 are recommended, providing practical guidance for night lighting design in residential areas. The innovation of this study lies in applying multi-objective optimization and K-means clustering to optimize the night lighting environment in micro-spaces within old multi-story residential areas in cities, offering new insights for lighting design in similar scenarios.