Analysing Populations of Design Variants Using Clustering and Archetypal Analysis

Abstract

In order to support exploration in the early stages of the design process, researchers have proposed the use ofpopulation-based multi-objective optimisation algorithms. This paper focuses on analysing the resulting population of design variants in order to gain insights into the relationship between architectural features and design performance. The proposed analysis method uses a combination of k-means clustering and Archetypal Analysis in order to partition the population of design variants into clusters and then to extract exemplars for each cluster. The results of the analysis are then visualised as a set of charts and as design models. A demonstration of the method is presented that explores how self-shading geometry, envelope materials, and window area affect the overall performance of a simplified building type. The demonstration shows that although it is possible to derive general knowledge linking architectural features to design performance, the process is still not straightforward. The paper ends with a discussion on how the method can be further improved.