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This paper presents an approach for optimizing floor plans using data collected from workplaces and a physics-based planning algorithm utilizing GPU-acceleration. The approach is compared to two approaches based on Genetic Algorithms and Particle Swarm Optimization. Common objectives, such as minimizing distance between related departments and daylight usage are optimized using the physics-based method in a case study of an actual plot and company. The results show that the physics-based approach is very efficient at handling large amounts of rooms compared to the other methods tested.

GPU-Enabled Physics-Based Floor Plan Optimization Based on Work Place Analytical Data