Advances in Bayesian Optimization with Applications in Aerospace Engineering
Optimization requires the quantities of interest that define objective functions and constraints to be evaluated a large number of times. In aerospace engineering, these quantities of interest can be expensive to compute (e.g., numerically solving a set of partial differential equations), leading to...
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Article |
| Language: | en_US |
| Published: |
American Institute of Aeronautics and Astronautics
2018
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| Online Access: | http://hdl.handle.net/1721.1/116471 https://orcid.org/0000-0003-4222-5358 https://orcid.org/0000-0003-2156-9338 |