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Multi-fidelity optimization via surrogate modelling

Multi-fidelity optimization via surrogate modelling
Multi-fidelity optimization via surrogate modelling
This paper demonstrates the application of correlated Gaussian process based approximations to optimization where multiple levels of analysis are available, using an extension to the geostatistical method of co-kriging. An exchange algorithm is used to choose which points of the search space to sample within each level of analysis. The derivation of the co-kriging equations is presented in an intuitive manner, along with a new variance estimator to account for varying degrees of computational ‘noise’ in the multiple levels of analysis. A multi-fidelity wing optimization is used to demonstrate the methodology.
co-kriging, kriging, noise, subset selection, wing design
1364-5021
3251-3269
Forrester, Alexander I.J.
176bf191-3fc2-46b4-80e0-9d9a0cd7a572
Sóbester, András
096857b0-cad6-45ae-9ae6-e66b8cc5d81b
Keane, Andy J.
26d7fa33-5415-4910-89d8-fb3620413def
Forrester, Alexander I.J.
176bf191-3fc2-46b4-80e0-9d9a0cd7a572
Sóbester, András
096857b0-cad6-45ae-9ae6-e66b8cc5d81b
Keane, Andy J.
26d7fa33-5415-4910-89d8-fb3620413def

Forrester, Alexander I.J., Sóbester, András and Keane, Andy J. (2007) Multi-fidelity optimization via surrogate modelling. Proceedings of the Royal Society A, 463 (2088), 3251-3269. (doi:10.1098/rspa.2007.1900).

Record type: Article

Abstract

This paper demonstrates the application of correlated Gaussian process based approximations to optimization where multiple levels of analysis are available, using an extension to the geostatistical method of co-kriging. An exchange algorithm is used to choose which points of the search space to sample within each level of analysis. The derivation of the co-kriging equations is presented in an intuitive manner, along with a new variance estimator to account for varying degrees of computational ‘noise’ in the multiple levels of analysis. A multi-fidelity wing optimization is used to demonstrate the methodology.

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More information

Published date: 8 December 2007
Keywords: co-kriging, kriging, noise, subset selection, wing design

Identifiers

Local EPrints ID: 64698
URI: https://eprints.soton.ac.uk/id/eprint/64698
ISSN: 1364-5021
PURE UUID: f5bb57a4-d2f0-4d1a-8283-d75456b5c831
ORCID for András Sóbester: ORCID iD orcid.org/0000-0002-8997-4375

Catalogue record

Date deposited: 09 Jan 2009
Last modified: 17 Sep 2019 01:00

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