Abstract: As the construction industry undergoes digital transformation and smart home environments continue to evolve, the demand for automated layout solutions for home appliances and furniture has grown significantly. Introduces an interior layout optimization method that integrates prior knowledge with Particle Swarm Optimization (PSO) to enable efficient and intelligent spatial arrangement. Initially, major furniture and appliance objects are grouped based on spatial semantic rules, allowing a rule-driven system to generate a reasonable initial placement. A multi-objective cost function is then formulated, incorporating both object-to-object relationships and spatial constraints derived from floor plan structures. PSO is applied to iteratively optimize the layout across the entire space. By leveraging structural layout information and predefined item groupings, the method enhances both the accuracy of the initial arrangement and the convergence speed of the optimization process. The approach balances individual object placement with overall spatial harmony. Experimental results show that the generated layouts are both practical and esthetically comparable to manually designed configurations. This work exemplifies the application of artificial intelligence algorithms in the optimization of furniture and appliance layouts, and holds strong potential for deployment in smart home design systems.

Key words: Interior design, Automatic layout, Prior knowledge, Particle swarm optimization