Computational approaches to space planning: A systematic review of enhancing architectural layouts

Abstract

In architectural design, a well-structured and adaptable approach is fundamental to creating functional and cohesive spaces, providing a foundational framework for spatial organization. As design requirements grow increasingly complex, traditional methods often fall short of addressing multifaceted design needs, such as user preferences, environmental considerations, and geometric constraints. Computational design techniques offer advanced methods to automate and refine architectural space planning. Despite significant advancements in computational software and data processing capabilities, challenges remain in practically embedding diverse design criteria. This study systematically reviews computational methods for architectural spatial design from 2013 to 2023, analyzing methodologies, typological applications, user preferences, and advancements in environmental data integration. The findings highlight a shift from rule-based to data-driven approaches, emphasizing the development of scalable and intuitive tools. This research identifies pathways for adopting computational design in architectural practice and education, underlining the critical role of user-centered adaptability and environmental responsiveness in shaping future tools.