An integrated generative-analytic framework for the performance-driven design of kinetic façades

Purpose This research introduces a two-stage optimization methodology for adaptive kinetic façades, prioritizing performance objectives to address occupant comfort and energy efficiency. The study explores various façade morphologies to tackle multiple, often conflicting, objectives. By progressively increasing design parameters, the methodology identifies optimal solutions through multi-criteria decision-making. Design/methodology/approach This study used parametric thinking to design a high-performance kinetic façade through four steps: (1) Identifying parameters (outdoor climate, building traits and occupant behavior); (2) Creatively synthesizing these into an innovative façade design; (3) Evaluating performance via visual/thermal comfort, energy use and daylight metrics; and (4) Optimizing solutions through multi-objective simulations and decision-making. The approach balanced conflicting goals, providing a structured tool for early design decisions. The computational workflow maximizes visual and thermal comfort, daylight performance and view quality, while minimizing energy consumption and solar heat gain (SHG). It categorizes objectives into primary and secondary groups and uses genetic algorithms with TOPSIS analysis for MCDM. Findings Key findings demonstrate remarkable performance, including 0% annual solar exposure, high useful daylight illuminance (80.4%) and spatial daylight autonomy (81.25%), good spatial glare autonomy (85%) and view factor (42.6%) and zero hot discomfort due to reduced SHG. The system achieved significant energy reductions (68.99–85.37%) through integrated daylighting and dimmable electric lighting controls, alongside a 10.60% reduction in cooling loads. Originality/value This pioneering computational workflow is the first control logic for unconventional façades that simultaneously considers multiple influential objectives in optimization. It transitions from low to high parameter numbers to identify optimal solutions using precise MCDM, integrating benchmarking, post-processing and objective weighting. This approach supports informed decision-making for adaptable, comfortable, energy-efficient and glare-free spaces.