Research on intelligent interior design optimization system based on AI algorithm

This study proposes an intelligent interior design optimization system based on AI algorithm. By constructing a multi-objective optimization model integrating space utilization, style consistency and economic indicators, a hybrid genetic algorithm is used to achieve the coordinated optimization of functional layout and aesthetic requirements. The system integrates ResNet-50 style feature extraction, rasterized space encoding and ONNX accelerated reasoning technology to convert the floor plan and preference image input by the user into a computable parametric representation. In 1,950 tests, it achieved an average space utilization rate of 82.4% and a cost deviation rate of 8.7%. The response time is less than 0.5 seconds, and it supports real-time 3D interaction with thousands of people. Experiments show that compared with traditional CAD tools, this system has significant advantages in space utilization efficiency and cost control, and provides an engineering solution for intelligent interior design.