Profit-sensitive generative design for high-rise building morphologies: innovations in 3D form generation and cost-revenue assessment

Abstract

ABSTRACT Generative design has been applied to facilitate architectural exploration and augment designers’ ability to consider building profits. However, the take-up of generative design instruments is slow due to the lack of considering practical needs. This paper reports a novel generative design methodology that meets the practical needs of profit-aware morphology for high-rise buildings. It follows a generation–evaluation–optimization workflow but is enriched with a novel shape generator; an evaluator estimating construction cost and selling revenue; and an optimizer using genetic algorithms. The methodology is prototyped in Grasshopper with Python programs embedded and then tested in two real cases in Hong Kong. We find that the methodology is effective in generating complex yet plausible morphologies for high-rises, evaluating their costs and revenues, and deriving profit-optimal buildings. This research contributes to the growing literature on generative design and could lead to a practical design tool that bridges designers and surveying professions.