WP145: Exploring Methods to Quantitatively Compare Optimization Techniques for Building Envelope Design
Abstract/Contents
- Abstract
Building designers often face tradeoffs when comparing designs that are not readily reducible to single objective functions, but instead benefit from evaluating multiple objectives, this is especially true for building envelope design. Multiple Objective Optimization (MOO) methods are available to assist designers to systematically search through large numbers of design
alternatives to identify high-performing design solutions in terms of two or more objectives. This paper evaluates three genetic algorithms (GAs) and a gradient-based algorithm that designs various elements of a building's envelope attempting to minimize both life-cycle costs (LCCs) and environmental impact. We evaluated the solution quality of each algorithm in
terms of multiple performance indicators, and various convergence criteria. The results show that the Darwin and DAKOTA GAs are consistently top performers. The evaluation also demonstrates the value of the hyperarea as a dual objective indicator of solution quality and synthesizes much of the available literature on the metrics of multiobjective solution quality.
Description
Type of resource | text |
---|---|
Date created | September 2019 |
Creators/Contributors
Author | Barg, Steve | |
---|---|---|
Author | Flager, Forest | |
Author | Fischer, Martin |
Subjects
Subject | Building design |
---|---|
Subject | building envelope |
Subject | algorithm evaluation |
Subject | multiobjective optimization |
Genre | Technical report |
Bibliographic information
Access conditions
- Use and reproduction
- User agrees that, where applicable, content will not be used to identify or to otherwise infringe the privacy or confidentiality rights of individuals. Content distributed via the Stanford Digital Repository may be subject to additional license and use restrictions applied by the depositor.
Collection
CIFE Publications
View other items in this collection in SearchWorksContact information
- Contact
- cife-email@stanford.edu
Also listed in
Loading usage metrics...