Parametric building information modelling and optimality criteria methods for automated multi-objective optimisation of structural and energy efficiency

Modern high-rise buildings have complex and irregular envelope geometrics, which pose large uncertainty on the structural behaviour and energy performance. There have been limited attempts, and previous studies which targeted the optimisation of structural elements did not address the association of individual elements with the envelope shape of the overall building. This study presents a new Parametric BIM-based Optimality Criteria (PBIM-OC) method that enables multi-objective optimisation of envelope shape and element size for tall buildings. The study proposes a comprehensive parameterisation method to describe the complex geometrics of envelope shapes for high-rise buildings. The non-dominated sorting genetic algorithm (NSGA) and multi-objective genetic algorithm (MOGA) were used to conduct multi-objective optimisation, providing optimal solutions for envelope shapes that maximise structural cost and operating energy efficiencies. The illustrative examples show a structurally inefficient building shape design can lead to a 60% of structural cost difference. This study contributes a new parametric optimisation method that explores optimal designs and investigates the influence of geometric changes in building envelopes on performance solutions. The results provide insights into the relationship between building envelopes and structural efficiency, highlighting the trade-off between structural material cost and energy performance of high-rise buildings. Overall, this research provides valuable information for the construction industry to design tall buildings that are more efficient and cost-effective.