Genetic algorithm-based assessment of kinetic façade prototypes for energy optimization and user comfort: a hotel case study in Iran

Hotel buildings in hot-humid climates face complex design challenges due to continuous occupancy, diverse functional spaces, and high demands for energy efficiency and occupant comfort. This study investigated how kinetic façade systems can address these challenges by dynamically adapting to environmental conditions. Three façade prototypes—a hexagonal rotating panel system, a Rec-Tri Pro sliding system, and the Al Bahar design inspired by Islamic geometric principles—were modeled and evaluated using environmental simulation tools in Grasshopper (Ladybug and Honeybee). A multi-objective genetic algorithm (Octopus) was employed to perform more than 1800 simulation-based optimization runs. Performance was assessed using four indicators: Energy Use Intensity (EUI), Daylight Autonomy (DA), Discomfort Glare Probability (DGP), and Predicted Mean Vote (PMV). The results indicate that each façade system demonstrated distinct performance strengths. The Al Bahar configuration exhibited the most balanced overall performance, achieving high daylight autonomy (74.8%), controlled glare levels (DGP < 0.35), and stable thermal comfort (PMV ranging between − 0.1 and + 0.4). In contrast, the Rec-Tri system achieved the lowest optimized energy consumption (~ 104.8 kWh/m2). These conclusions are based on a comparative multi-criteria assessment rather than prioritizing a single performance indicator. This study proposed a replicable five-stage framework to support the early-stage design and optimization of responsive kinetic façades in hospitality buildings through integrated simulation and standardized comparative evaluation methods.