Meta-parametric design

Harding, John; Shepherd, Paul

Abstract

© 2016 Elsevier Ltd Parametric modelling software often maintains an explicit history of design development in the form of a graph. However, as the graph increases in complexity it quickly becomes inflexible and unsuitable for exploring a wide design space. By contrast, implicit low-level rule systems can offer wide design exploration due to their lack of structure, but often act as black boxes to human observers with only initial conditions and final designs cognisable. In response to these two extremes, the authors propose a new approach called Meta-Parametric Design, combining graph-based parametric modelling with genetic programming. The advantages of this approach are demonstrated using two real case-study projects that widen design exploration whilst maintaining the benefits of a graph representation.

• Journal Article Type: Article
• Acceptance Date: Oct 5, 2016
• Online Publication Date: Oct 18, 2016
• Publication Date: Sep 1, 2017
• Deposit Date: Oct 25, 2016
• Publicly Available Date: Oct 18, 2017
• Journal: Design Studies
• Print ISSN: 0142-694X
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 52
• Pages: 73-95
• DOI: https://doi.org/10.1016/j.destud.2016.09.005
• Keywords: parametric design, conceptual design, design cognition, human–computer interaction, genetic programming
• Public URL: https://uwe-repository.worktribe.com/output/881237
• Publisher URL: http://dx.doi.org/10.1016/j.destud.2016.09.005
• Contract Date: Oct 25, 2016