A Generative Design Approach To Urban Sustainability Rating Systems During Early-Stage Urban Development
Sustainability rating systems (SRS) aim to guide decision-makers in the planning process by defining clear guidelines and metrics. Nowadays, this process usually requires further tasks and the involvement of multiple professional advisors that eventually increase planning complexity and lead to lower SRS implementation. In this paper, we explore generative urban models and multi-objective optimization of SRS metrics to potentially enhance SRS use in planning processes. Furthermore, we apply this framework to a case study that has not reached its SRS planning goals due to contradicting trade-offs between municipal and stakeholder objectives. The urban model reflects the stakeholder design requirements and constraints such as the desired floor area ratio (FAR), building types, and units’ number while the SRS metrics act as optimization goals. As part of the process, we automate quantitative indicators from Israel SRS ‘360 Neighbourhood’ to use them as optimization goals and to analyse their correlation and trade-offs. Through this process, we enable a generative exploration of high-performing design iterations relative to a chosen set of SRS goals. Such a framework can enhance the integration of verified sustainability goals in the planning process, thus informing the stakeholders of their decision trade-off’s concerning SRS indicators in urban development.
Keywords: Sustainability Rating Systems; Generative Design; Multi-Objective Optimization; Urban Modelling And Simulation; Sdg 11