An Automated Pipeline for Modular Space Planning Using Generative Design Within a BIM Environment

Spatial Allocation Problems (SAP) in multistory buildings present significant challenges, as they require the simultaneous satisfaction of complex geometric constraints and conflicting functional requirements. To address this problem, this study proposes an integrated pipeline utilizing Generative Design (GD) methodologies within a Building Information Modeling (BIM) environment to automate and optimize a 3.3 m modular multi-story spatial allocation. The core of the proposed methodology lies in the clear distinction and application of design requirements formalized as ‘Hard Constraints’ (mandatory conditions for feasibility) and ’Soft Objectives’ (metrics for performance evaluation). Hard constraints include the implementation of a boundary constraint, ensuring that all spaces remain within defined limits, and a vertical alignment constraint for fixed elements (e.g., cores), thereby ensuring geometric and structural validity. To quantify functional efficiency, three soft objectives were defined: positional preference, circulation efficiency, and functional cohesion. The methodology was validated using a four-story case study. The implemented system successfully generated numerous valid design alternatives that satisfied all hard constraints while simultaneously optimizing the three soft objectives. Aimed at architects, building designers, and computational specialists, this study offers significant practical value by providing a tool that automates the complex initial phases of space planning. This allows designers to rapidly explore and quantitatively evaluate a wide array of optimized and valid layouts. This study contributes to a systematic framework for balancing geometric validity and functional efficiency during the early design stages by presenting a concrete procedure for integrating GD and BIM to solve complex SAPs.