Design optimisation study of indoor environments in student dormitories with enclosed balconies through multi-algorithm integration

Student dormitories often face indoor environmental challenges due to high occupant density, functional demands and spatial constraints. This study explored trade-offs between indoor comfort and energy consumption through a holistic envelope design. A university dormitory with enclosed balconies in China was used as a case study, and a multidimensional optimisation framework for windows, shading devices and balconies was developed by integrating field measurements, simulation and algorithmic analysis. Indoor environmental conditions and energy performance were simulated using Ladybug, Honeybee and Butterfly. The extreme gradient boosting (XGBoost) model was combined with an improved decomposition-based multi-objective evolutionary algorithm (IMOEA/D) to predict and optimise thermal comfort, natural ventilation and energy use, whilst analysing the influence of envelope parameters on indoor environmental quality. Pareto front solutions were screened using the entropy weight-technique for order preference by similarity to ideal solution (EW-TOPSIS) method, yielding optimal ranges: an external window-to-wall ratio (EWWR) of 0.44–0.55, an internal window-to-wall ratio (IWWR) of 0.31–0.36, shading height (SH) of 2.8–3.18 m, shading width (SW) of 0.60–0.71 m, enclosed balcony depth (EBD) of 1.61–1.79 m, and floor height (FH) of 8.06–16.29 m. The study also examined building orientation effects. This research provides an efficient, systematic method for integrated envelope design and retrofit in student dormitories, targeting enhanced indoor health, comfort and energy efficiency.