Algorithmic generation of architectural massing models for building design optimisation: Parametric modelling using subtractive and additive form generation principles

Abstract

Using performance-based optimisation to explore unknown design solutions space has become widely acknowledged and considered an efficient approach to designing high-performing buildings. However, the lack of design diversity in the design space defined by the parametric model often confines the search of the optimisation process to a family of similar design variants. In order to overcome this weakness, this paper presents two parametric massing generation algorithms based on the additive and subtractive form generation principles. By abstracting the rule of these two principles, the algorithms can generate diverse building massing design alternatives. This allows the algorithms to be used in performance-based optimisation for exploring a wide range of design alternatives guided by various performance objectives. Two case studies of passive solar energy optimisation are presented to demonstrate the efficacy of the algorithm in helping architects achieve an explorative performance-based optimisation process.