Multiobjective Pareto optimization of electromagnetic devices exploiting hybrid kriging
Multiobjective Pareto optimization of electromagnetic devices exploiting hybrid kriging
The paper focuses on resolving the storage issue of correlation matrices generated by kriging surrogate models in the context of electromagnetic optimization problems with many design variables and multiple objectives. A hybrid kriging approach that involves a direct algorithm in kriging is able to maintain memory requirements at a nearly constant level while offering high efficiency of searching for a global optimum. The feasibility and efficiency of this proposed methodology is demonstrated using an example of a classic two-variable analytic function and a new proposed benchmark TEAM multi-objective pareto optimization problem.
Kriging surrogate model, correlation matrices, hybrid kriging, direct algorithm, multi-objective pareto optimization
Xiao, Song
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Liu, G. Q.
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Zhang, K. L.
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Jing, Y. Z.
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Duan, J. H.
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Di Barba, Paolo
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Sykulski, Jan
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June 2017
Xiao, Song
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Liu, G. Q.
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Zhang, K. L.
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Jing, Y. Z.
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Duan, J. H.
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Di Barba, Paolo
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Sykulski, Jan
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Xiao, Song, Liu, G. Q., Zhang, K. L., Jing, Y. Z., Duan, J. H., Di Barba, Paolo and Sykulski, Jan
(2017)
Multiobjective Pareto optimization of electromagnetic devices exploiting hybrid kriging.
21st International Conference on the Computation of Electromagnetic Fields, Daejeon Convention Center, Daejeon, Korea, Republic of.
18 - 22 Jun 2017.
2 pp
.
Record type:
Conference or Workshop Item
(Paper)
Abstract
The paper focuses on resolving the storage issue of correlation matrices generated by kriging surrogate models in the context of electromagnetic optimization problems with many design variables and multiple objectives. A hybrid kriging approach that involves a direct algorithm in kriging is able to maintain memory requirements at a nearly constant level while offering high efficiency of searching for a global optimum. The feasibility and efficiency of this proposed methodology is demonstrated using an example of a classic two-variable analytic function and a new proposed benchmark TEAM multi-objective pareto optimization problem.
Text
COMPUMAG2017Digest(Song_Xiao)
- Accepted Manuscript
More information
Accepted/In Press date: 8 March 2017
Published date: June 2017
Venue - Dates:
21st International Conference on the Computation of Electromagnetic Fields, Daejeon Convention Center, Daejeon, Korea, Republic of, 2017-06-18 - 2017-06-22
Keywords:
Kriging surrogate model, correlation matrices, hybrid kriging, direct algorithm, multi-objective pareto optimization
Organisations:
EEE
Identifiers
Local EPrints ID: 408113
URI: http://eprints.soton.ac.uk/id/eprint/408113
PURE UUID: 5c67f7d1-381f-42f3-86aa-39b45c31285c
Catalogue record
Date deposited: 12 May 2017 04:03
Last modified: 16 Mar 2024 02:34
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Contributors
Author:
Song Xiao
Author:
G. Q. Liu
Author:
K. L. Zhang
Author:
Y. Z. Jing
Author:
J. H. Duan
Author:
Paolo Di Barba
Author:
Jan Sykulski
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