Generative Design in the Built Environment
Zhi Xian Chew, Jing Ying Wong, Yu Hoe Tang, Chun Chieh Yip, Tomás Maul
Abstract
Generative design (GD) has gained widespread attention in the built environment domain, revolutionising traditional methodologies in the field. It operates on a set of rules, utilising algorithmic and parametric modelling techniques to explore and enhance design options. By determining the existing challenges and ongoing research in 85 representative papers, this paper seeks to explore the implications of GD within built environment, sustainability, BIM, and AI design practices, clarifying its potential to shape a more sustainable, resilient, and inclusive built environment for future generations. It contributes to the dialogue surrounding the utilisation of GD as a tool for building and infrastructure design practices via a content analysis-based review method. Incorporating advanced technologies could facilitate a more effective and immediate response to design methodologies, thus promoting enhanced innovation and sustainability in design practices. The selection of, and proficiency in, programming languages constitute important aspects in advancing GD aligned with built environment objectives. • Content analysis-based review of 85 publications categorised into built environment, sustainability, Building Information Modelling (BIM), and AI design practices. • Positive trend in generative design applications, with textual programming languages (TPL) still prevalent but virtual programming languages (VPL) gaining attention. • Hybrid Programming Approach for Generative Design (HyPAGeD), combining TPL and VPL. • Integration of AI algorithms becoming instrumental in optimizing and innovating design processes. • Relationship between generative design and its application across structural design, construction, infrastructure, environment, prefabrication, hydraulics, geotechnics, and urban planning, highlighting generative design's effectiveness in various design methods.