Optimizing Creatively in Multi-Objective Optimization
Yassin Ashour and Branko Kolarevic
EVDS, University of Calgary
Calgary, AB, Canada
Designers will always face the challenge of designing well- performing buildings using what are often conflicting and competing objectives. Early stage design decisions influence significantly the final performance of a building and designers are often unable to explore large numbers of design alternatives with respect to the performative criteria set for the project. This research by Yassin Ashour and Branko Kolarevic outlines a “creative optimization workflow” using a Multi-Objective Optimization (MOO) engine called Octopus that runs within Grasshopper3D, a parametric modeling tool, and simulation software DIVA for daylight factor analysis.
The workflow utilizes a “creative optimization tool” which allows the designer to explore, sort and filter solutions, and analyze both quantitatively and qualitatively the trade-offs of the resultant design solution space. It enables the designer to visually compare alternative solutions in a gallery and subsequently analyze trade-offs through a radar- based chart, parallel coordinate plot graphs and conditional domain searches. This feedback tools allows the designer to quickly and efficiently identify potential solutions for either design development or to select preferred solutions for further optimization, i.e. “optimizing creatively”.
A retrospective design case study, the “De Rotterdam” building, is used to demonstrate the application of the tools. The workflow demonstrates the ability to reduce design latency and to allow for better understanding of design solutions. Additional research is needed to better understand the application of MOO in the early stages of design; and the further improvement of the creative optimization tools to accommodate the designer’s need for a more dynamic and synergistic process.