Abstract
We address the problem of simulation-based design using multiple interconnected expensive simulation models, each modeling a different subsystem. Our goal is to find the globally optimal design with minimal model evaluation costs. To our knowledge, the best existing approach is to treat the whole system as a single expensive model and apply an existing Bayesian optimization (BO) algorithm. This approach is likely inefficient due to the need to evaluate all the component models in each iteration. We propose a multi-model BO approach that dynamically and selectively evaluates one component model per iteration based on linked emulators for uncertainty quantification and the system knowledge gradient (KG) as acquisition function. Building on this, we resolve problems with constraints and feedback couplings that often occur in real complex engineering design by penalizing the objective emulator and reformulating the original problem into a decoupled one. The superior efficiency of our approach is demonstrated through solving an analytical problem and a multidisciplinary design problem of electronic packaging optimization.
Original language | English (US) |
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Title of host publication | 46th Design Automation Conference (DAC) |
Publisher | American Society of Mechanical Engineers (ASME) |
ISBN (Electronic) | 9780791884010 |
DOIs | |
State | Published - 2020 |
Event | ASME 2020 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC-CIE 2020 - Virtual, Online Duration: Aug 17 2020 → Aug 19 2020 |
Publication series
Name | Proceedings of the ASME Design Engineering Technical Conference |
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Volume | 11B-2020 |
Conference
Conference | ASME 2020 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC-CIE 2020 |
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City | Virtual, Online |
Period | 8/17/20 → 8/19/20 |
Funding
The grant support from the National Science Foundation (CMMI-1662435) is greatly appreciated.
ASJC Scopus subject areas
- Mechanical Engineering
- Computer Graphics and Computer-Aided Design
- Computer Science Applications
- Modeling and Simulation