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A Knowledge-Based Approach to Problem Formulation for Product Model-Based Multidisciplinary Design Optimization in AEC

TitleA Knowledge-Based Approach to Problem Formulation for Product Model-Based Multidisciplinary Design Optimization in AEC
Publication TypeConference Paper
Year of Publication2011
AuthorsWelle, B, Haymaker, J
Date Published03/2011
Keywordsartificial intelligence, building simulation, Center for Integrated Facility Engineering, CIFE, Conceptual Building Design, design automation, energy-efficient buildings, knowledge-based systems, multidisciplinary design optimization (MDO), problem formulation, Stanford University
AbstractThe 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.
URLhttps://purl.stanford.edu/qb779jh9716