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Correlation matrices in kriging assisted optimisation of electromagnetic devices

Correlation matrices in kriging assisted optimisation of electromagnetic devices
Correlation matrices in kriging assisted optimisation of electromagnetic devices
Kriging surrogate modelling facilitates efficient decision making regarding where to place the next point for evaluation during optimisation. This is particularly helpful in the design of electromagnetic devices where computationally expensive numerical field modelling needs to be used. The disadvantage, however, is that correlation matrices are required which, for problems with many design variables and multiple objectives, may grow in size leading to the need for page swapping and thus slowing down of what in principle should be a very fast process. In this study several methodologies to reduce the computational resources required in such problems are proposed. The efficiency of the proposed approach is demonstrated using an example of a large multi-parameter optimisation problem where kriging coupled with the average gradient value method is employed.
optimisation, matrix algebra, statistical analysis, electromagnetic devices
1751-8830
189-196
Xiao, Song
6ffa9657-513e-4b86-86a2-e560d3c09c72
Rotaru, M.
c53c5038-2fed-4ace-8fad-9f95d4c95b7e
Sykulski, J. K.
d6885caf-aaed-4d12-9ef3-46c4c3bbd7fb
Xiao, Song
6ffa9657-513e-4b86-86a2-e560d3c09c72
Rotaru, M.
c53c5038-2fed-4ace-8fad-9f95d4c95b7e
Sykulski, J. K.
d6885caf-aaed-4d12-9ef3-46c4c3bbd7fb

Xiao, Song, Rotaru, M. and Sykulski, J. K. (2015) Correlation matrices in kriging assisted optimisation of electromagnetic devices. IET Science, Measurement & Technology, 9 (2), 189-196. (doi:10.1049/iet-smt.2014.0194).

Record type: Article

Abstract

Kriging surrogate modelling facilitates efficient decision making regarding where to place the next point for evaluation during optimisation. This is particularly helpful in the design of electromagnetic devices where computationally expensive numerical field modelling needs to be used. The disadvantage, however, is that correlation matrices are required which, for problems with many design variables and multiple objectives, may grow in size leading to the need for page swapping and thus slowing down of what in principle should be a very fast process. In this study several methodologies to reduce the computational resources required in such problems are proposed. The efficiency of the proposed approach is demonstrated using an example of a large multi-parameter optimisation problem where kriging coupled with the average gradient value method is employed.

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Accepted/In Press date: 29 September 2014
Published date: 11 March 2015
Keywords: optimisation, matrix algebra, statistical analysis, electromagnetic devices
Organisations: EEE

Identifiers

Local EPrints ID: 375073
URI: http://eprints.soton.ac.uk/id/eprint/375073
ISSN: 1751-8830
PURE UUID: c4cb1e34-6e92-4e91-8a99-714c11a5c992
ORCID for J. K. Sykulski: ORCID iD orcid.org/0000-0001-6392-126X

Catalogue record

Date deposited: 11 Mar 2015 10:11
Last modified: 07 Oct 2020 02:27

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