The University of Southampton
University of Southampton Institutional Repository

Non-stationary kriging for design optimization

Non-stationary kriging for design optimization
Non-stationary kriging for design optimization
Traditional surrogate modeling techniques, such as kriging, have been employed quite effectively within design optimizations. However, such models can fail to accurately reproduce non-stationary responses. The following paper explores the application of non-stationary kriging to design optimization and attempts to determine its applicability with regard to the optimization of both stationary and non-stationary objective functions. A series of analytical test problems and an engineering design problem are used to compare the performance of non-stationary and adaptive partial non-stationary kriging to traditional stationary kriging.
non-stationary kriging, surrogate modelling, optimization
741-765
Toal, D.J.J.
dc67543d-69d2-4f27-a469-42195fa31a68
Keane, A.J.
26d7fa33-5415-4910-89d8-fb3620413def
Toal, D.J.J.
dc67543d-69d2-4f27-a469-42195fa31a68
Keane, A.J.
26d7fa33-5415-4910-89d8-fb3620413def

Toal, D.J.J. and Keane, A.J. (2011) Non-stationary kriging for design optimization. Engineering Optimization, 44 (6), 741-765. (doi:10.1080/0305215X.2011.607816).

Record type: Article

Abstract

Traditional surrogate modeling techniques, such as kriging, have been employed quite effectively within design optimizations. However, such models can fail to accurately reproduce non-stationary responses. The following paper explores the application of non-stationary kriging to design optimization and attempts to determine its applicability with regard to the optimization of both stationary and non-stationary objective functions. A series of analytical test problems and an engineering design problem are used to compare the performance of non-stationary and adaptive partial non-stationary kriging to traditional stationary kriging.

Text
non-stationary_surrogate_modelling_for_design_optimization(final).pdf - Author's Original
Restricted to Repository staff only
Request a copy

More information

Published date: 23 September 2011
Keywords: non-stationary kriging, surrogate modelling, optimization
Organisations: Computational Engineering & Design Group

Identifiers

Local EPrints ID: 340898
URI: http://eprints.soton.ac.uk/id/eprint/340898
PURE UUID: 55444c15-117b-472c-a009-b31d5f402222
ORCID for D.J.J. Toal: ORCID iD orcid.org/0000-0002-2203-0302
ORCID for A.J. Keane: ORCID iD orcid.org/0000-0001-7993-1569

Catalogue record

Date deposited: 06 Jul 2012 11:12
Last modified: 15 Mar 2024 03:29

Export record

Altmetrics

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×