Interior Space Layout Optimization and Intelligent Design Based on Genetic Algorithm

Due to its extensive potential applications and substantial commercial value, indoor spatial arrangement has emerged as a prominent research domain within the realms of computer graphics and computer vision. In the domain of indoor spatial arrangement, the task commonly entails the creation or enhancement of layouts within a specified area or space. This article primarily concentrates on the optimization and automated design of indoor spatial arrangements, presenting novel approaches to rectify the limitations encountered by current algorithms. Specifically, this article introduces an optimization methodology grounded in design constraints that facilitates the automated generation of layout plans. Given the external contour of the building, in order to automatically generate the internal space layout, the solution of this study is a mixed integer quadratic programming (MIQP)-based indoor space layout design method. In addition, this piece picks out a few key design constraints, which it then uses to model the MIQP issue in its conventional form so that it fits our parameterized form. This work proposes an assessment approach based on the GA-BP algorithm to measure the efficacy of the strategy. Multiple experiments show that the method suggested in this research works for large-scale scene layouts, as well as for the automated optimisation design of residential structures’ interior spaces. The final experimental results and analysis indicate that the method proposed in this paper has much higher computational efficiency and quality than traditional random optimization methods.