Interior lighting design and environmental art effect optimization based on genetic algorithm

Abstract

This article aims to solve the problems of strong subjectivity and single design optimization objectives in interior lighting design through optimization methods based on genetic algorithm (GA), in order to improve the artistic effect and user experience of interior environment. This article first analyzes the functions and user needs of interior spaces, determines the basic principles and goals of lighting design, and then uses GA to encode and optimize parameters such as the position, brightness, color temperature, and direction of light sources. In the experimental stage, four rooms with the same layout are selected, and relevant data is collected and analyzed by comparing the lighting design based on GA optimization with the other three design methods (empirical method, normative method, and computational method) in terms of lighting uniformity, energy consumption, visual comfort, and artistic effects. The experimental results show that the room optimized by GA performs the best in terms of lighting uniformity, with a standard deviation of only 5.86; in terms of energy consumption, it is the lowest, with a 5-day energy consumption of 12.5 kilowatt-hours, 11.9 kilowatt-hours, 12.3 kilowatt-hours, 12.1 kilowatt-hours, and 12.2 kilowatt-hours, respectively; it achieves the highest score in terms of visual comfort, with the number of high scores exceeding that of other rooms. At the same time, it also obtains the highest evaluation score in the environmental art effect test. These data indicate that the GA optimization method has significant advantages in improving the overall effect of interior lighting design, and can effectively balance the artistic effect and functional requirements of interior environments.