Application of Generative Design on Architecture to Optimize Design Decision in Preliminary Design Stage - Seto Maulana Mahendra; Usep Surahman; Aldissain Jurizat; Diah Sari (Journal of Artificial Intelligence in Architecture, 2025)
This study investigates the application of generative design through Autodesk Forma, a cloud-based AI platform, to optimise architectural decision-making in the preliminary design stage of a ten-story hotel in Cirebon City, Indonesia—a region characterised by a hot and humid climate. The research employed simulations based on five environmental parameters: sun hours, daylight potential, wind distribution, microclimate conditions, and solar energy. Three optimal models were selected based on orientation, spatial configuration, and environmental responsiveness. Subsequent development simulations were conducted on these three models by refining openings, adding vegetation, and enhancing shading strategies. Model-2 emerged as the best-performing design. It demonstrated an energy efficiency potential of approximately 23%, achieved through improved daylighting (VSC ≥ 27% on most facades), reduced reliance on artificial cooling due to stable microclimatic conditions (temperatures moderated by 2–3°C during peak hours), and the integration of solar panels generating an estimated 165,000 kWh/year from 40% roof coverage at 10% efficiency. The results confirm that AI-driven generative design can significantly accelerate the design process while enhancing environmental performance. This approach supports energy-efficient architecture in tropical regions, although it requires access to advanced technology, skilled practitioners, and robust internet connectivity.