Guiding early building design towards lower carbon emissions through set-based design and genetic algorithm optimisation

Purpose The materials used in the structural system account for a significant share of a building's total embodied carbon emissions. Thus, to mitigate the climate impact of construction projects, it is essential to consider carbon emissions in early conceptual design and understand how structural decisions affect costs. Therefore, this study explores integrating set-based design with genetic algorithm optimisation to evaluate a wide range of building designs in terms of cost and carbon performance. Design/methodology/approach First, databases of structural building assemblies, including their capacities, costs, and embodied carbon, were developed. The NSGA-II algorithm, combined with set-based design, was then applied to a reference building to minimise its cost and carbon emissions. Findings The genetic algorithm alone identified solutions that reduced carbon emissions by 35% but with a 9% increase in cost. When set-based design was incorporated, carbon emissions were reduced by up to 42% with a comparable increase in cost. The findings demonstrate that integrating set-based design offers comparative advantages over using genetic algorithms alone, providing valuable insights for early-stage building design practice. Originality/value This paper proposes a novel design approach that combines genetic algorithm optimisation with set-based design to explore a broader solution space and support data-informed decision-making to reduce carbon emissions in buildings.