Optimizing layout using spatial quality metrics and user preferences

Computational design is one of the most common tasks of immersive computer graphics projects, such as games, virtual reality and special effects. Layout planning is a challenging phase of architectural design, which requires optimization across several conflicting criteria. We present an interactive layout solver that assists designers in layout planning by recommending personalized space arrangements based on architectural guidelines and user preferences. Initialized by the designers high-level requirements, an interactive evolutionary algorithm is used to converge on an ideal layout by exploring the space of potential solutions. The major contributions of our proposed approach are addressing subjective aspects of the design to generate personalized layouts; and the development of a genetic algorithm with a multi-parental recombination method that improves the chance of generating higher quality offspring. We demonstrate the ability of our method to generate feasible floor plans which are satisfactory, based on spatial quality metrics and designers taste. The results show that the presented framework can measurably decrease planning complexity by producing layouts which exhibit characteristics of human-made design.