Generative design method of building group: Based on generative adversarial network and genetic algorithm

Abstract

From parametric shape finding to digital shape generation, the discussion of generative design has never stopped in recent years. As an important watershed of building intelligence, generative design method has dual significance of scheme selection and building performance optimization in digital architectural design workflow. In this paper, the generative design method for the layout of residential buildings is studied. The pix2pix network, a kind of generative adversarial network, is used to learn the layout method of residential buildings in Shanghai. The generated layout uses Octopus, a genetic algorithm tool of Grasshopper, to generate the volume and optimize the sunshine hours and other performance parameters. In the generation process, different training sample sets and Pareto genetic algorithm optimization are used to realize the control of building density, plot ratio and height limit. This method can meet the real application scenarios in the early stage of architectural design to a certain extent, and has more expansibility, providing ideas for the generative design method of building group.