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Abstract
A methodology for fast multi-objective antenna optimization is presented. Our approach is based on response surface approximation (RSA) modeling and variable-fidelity electromagnetic (EM) simulations. In the design process, a computationally cheap RSA surrogate model constructed from sampled coarse-discretization EM antenna simulations is optimized using a multi-objective evolutionary algorithm. The initially determined Pareto optimal set representing the best possible trade-offs between conflicting design objectives is then iteratively refined. In each iteration, a limited number of high-fidelity EM model responses are incorporated into the RSA model using co-kriging. The enhanced RSA model is subsequently re-optimized to yield the refined Pareto set. Combination of low- and high-fidelity simulations as well as co-kriging results in the low overall optimization cost. The proposed approach is validated using two UWB antenna examples.
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Authors (4)
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Ivo Couckuyt
- Department of Information Technology, Gent, Belgium Surrogate Modeling Lab
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Tom Dhaene
- Gent University, Gent, Belgium Surrogate Modeling Lab, Department of Information Technology
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Details
- Category:
- Articles
- Type:
- artykuł w czasopiśmie wyróżnionym w JCR
- Published in:
-
IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION
no. 62,
pages 5900 - 5905,
ISSN: 0018-926X - Language:
- English
- Publication year:
- 2014
- Bibliographic description:
- Kozieł S., Bekasiewicz A., Couckuyt I., Dhaene T.: Efficient Multi-Objective Simulation-Driven Antenna Design Using Co-Kriging// IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION. -Vol. 62, nr. 11 (2014), s.5900-5905
- DOI:
- Digital Object Identifier (open in new tab) 10.1109/tap.2014.2354673
- Verified by:
- Gdańsk University of Technology
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