REGEN: A Regulation-Aware Generative Design Framework for BIM-Enabled Multi-Objective Optimization of Sustainable Residential Buildings

Early-stage residential building design in dense urban environments involves complex interactions among zoning regulations, geometric configuration, environmental performance, and economic feasibility. Conventional CAD–spreadsheet workflows and parametric BIM-based approaches remain limited in systematically resolving these interdependent trade-offs and typically rely on heuristic iteration and post hoc regulatory verification. To address this limitation, this study proposes REGEN, a regulation-aware BIM-enabled multi-objective optimization framework for sustainable residential building design. The framework formalizes planning and building-control regulations as explicit algebraic constraints embedded within a parametric BIM environment and integrates them with the Non-dominated Sorting Genetic Algorithm II (NSGA-II) to generate regulation-compliant design alternatives with respect to the encoded planning and building-control regulations. REGEN simultaneously optimizes five competing objectives: maximizing project profit, green-area provision, and building efficiency while minimizing geometric shape factor and building footprint area. A real condominium feasibility case in Bangkok, Thailand, is used to benchmark the proposed framework against conventional practice and parametric BIM-based design under identical site and regulatory conditions. The results reveal a non-convex Pareto front that exposes complex trade-offs among environmental, geometric, and economic objectives. The selected closest-to-utopia solution achieves 65.50% building efficiency, 606 m2 of green area, a shape factor of 0.399, and a building footprint area of 1078 m2 while maintaining a competitive project profit of 104.55 million THB without maximizing FAR utilization. The findings suggest that regulation-aware generative optimization has the potential to serve as an explainable and decision-oriented approach for sustainable construction and early-stage residential development planning.