A constraint mapping approach to the structural optimization of an expensive model using surrogates (in special issue on surrogate modelling and space mapping for engineering optimization)
A constraint mapping approach to the structural optimization of an expensive model using surrogates (in special issue on surrogate modelling and space mapping for engineering optimization)
The use of response surface methods are well established in the global optimization of expensive functions, the response surface acting as a surrogate to the expensive function objective.
In structural design however, the change in objective may vary little between the two models: it is more often the constraints that change with models of varying fidelity. Here approaches are described whereby the coarse model constraints are mapped so that the mapped constraints more faithfully approximate the fine model constraints. The shape optimization of a simple structure demonstrates the approach.
kriging, space mapping, model fusion, expensive function optimization
385-398
Leary, Stephen J.
2f0f8880-bc29-4d3b-9af8-b66d759e4092
Bhaskar, Atul
d4122e7c-5bf3-415f-9846-5b0fed645f3e
Keane, Andy J.
26d7fa33-5415-4910-89d8-fb3620413def
2001
Leary, Stephen J.
2f0f8880-bc29-4d3b-9af8-b66d759e4092
Bhaskar, Atul
d4122e7c-5bf3-415f-9846-5b0fed645f3e
Keane, Andy J.
26d7fa33-5415-4910-89d8-fb3620413def
Leary, Stephen J., Bhaskar, Atul and Keane, Andy J.
(2001)
A constraint mapping approach to the structural optimization of an expensive model using surrogates (in special issue on surrogate modelling and space mapping for engineering optimization).
Optimization and Engineering, 2 (4), .
(doi:10.1023/A:1016038305014).
Abstract
The use of response surface methods are well established in the global optimization of expensive functions, the response surface acting as a surrogate to the expensive function objective.
In structural design however, the change in objective may vary little between the two models: it is more often the constraints that change with models of varying fidelity. Here approaches are described whereby the coarse model constraints are mapped so that the mapped constraints more faithfully approximate the fine model constraints. The shape optimization of a simple structure demonstrates the approach.
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lear_01.pdf
- Accepted Manuscript
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Published date: 2001
Keywords:
kriging, space mapping, model fusion, expensive function optimization
Identifiers
Local EPrints ID: 22064
URI: http://eprints.soton.ac.uk/id/eprint/22064
ISSN: 1389-4420
PURE UUID: f367be09-f4e2-4e98-859d-85bc1c8274d0
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Date deposited: 20 Mar 2006
Last modified: 16 Mar 2024 02:53
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Author:
Stephen J. Leary
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