Biomorpher: interactive evolution for parametric design

[thumbnail of 2018_IJAC_Preprint.pdf]
Preview
Text
- Accepted Version

Please see our End User Agreement.

It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing.

Add to AnyAdd to TwitterAdd to FacebookAdd to LinkedinAdd to PinterestAdd to Email

Harding, J. orcid id iconORCID: https://orcid.org/0000-0002-5253-5862 and Brandt-Olsen, C. (2018) Biomorpher: interactive evolution for parametric design. International Journal of Architectural Computing, 16 (2). pp. 144-163. ISSN 2048-3988 doi: 10.1177/1478077118778579

Abstract/Summary

Combining graph-based parametric design with metaheuristic solvers has to date focussed solely on performance based criteria and solving clearly defined objectives. In this paper, we outline a new method for combining a parametric modelling environment with an interactive Cluster-Orientated Genetic Algorithm (COGA). In addition to performance criteria, evolutionary design exploration can be guided through choice alone, with user motivation that cannot be easily defined. As well as numeric parameters forming a genotype, the evolution of whole parametric definitions is discussed through the use of genetic programming. Visualisation techniques that enable mixing small populations for interactive evolution with large populations for performance-based optimisation are discussed, with examples from both academia and industry showing a wide range of applications.

Altmetric Badge

Item Type Article
URI https://reading-clone.eprints-hosting.org/id/eprint/79580
Identification Number/DOI 10.1177/1478077118778579
Refereed Yes
Divisions Science > School of the Built Environment > Architecture
Science > School of the Built Environment > Urban Living group
Publisher Sage
Download/View statistics View download statistics for this item

Downloads

Downloads per month over past year

University Staff: Request a correction | Centaur Editors: Update this record

Search Google Scholar