A Knowledge-Based Approach to Problem Formulation for Product Model-Based Multidisciplinary Design Optimization in AEC
Abstract/Contents
- Abstract
- The cost-effectiveness and accuracy of a multidisciplinary design optimization (MDO) process is highly dependent on designers’ ability to flexibly formulate the optimization problem for specific challenges. Designers need to rapidly modify how object parameters are assigned to groupings of objects in the product model. Our research has developed a Reference-Based Optimization Method (RBOM) to enable this type of flexible problem formulation. However, the responsibility still falls on the designer to manage the problem formulation and MDO process, which can lead to inefficient and costly design decisions. By means of artificial intelligence, in particular knowledge-based systems, these potential barriers to MDO adoption in the Architecture, Engineering, and Construction (AEC) industry could be mitigated, resulting in more efficient design processes and, ultimately, energy-efficient built environments.
Description
| Type of resource | text |
|---|---|
| Date created | March 2011 |
Creators/Contributors
| Author | Welle, Benjamin |
|---|---|
| Author | Haymaker, John |
Subjects
| Subject | CIFE |
|---|---|
| Subject | Center for Integrated Facility Engineering |
| Subject | Stanford University |
| Subject | artificial intelligence |
| Subject | knowledge-based systems |
| Subject | multidisciplinary design optimization (MDO) |
| Subject | problem formulation |
| Subject | conceptual building design |
| Subject | building simulation |
| Subject | energy-efficient buildings |
| Subject | design automation |
| Genre | Conference publication |
Bibliographic information
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- Use and reproduction
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Preferred citation
- Preferred Citation
- WELLE, B.; HAYMAKER, J.. A Knowledge-Based Approach to Problem Formulation for Product Model-Based Multidisciplinary Design Optimization in AEC. AAAI Spring Symposium Series, North America, mar. 2011. Stanford Digital Repository. Available at: http://purl.stanford.edu/hj649dp5564
Collection
CIFE Publications
Contact information
- Contact
- cife-email@stanford.edu
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