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Abstract
A surrogate-based method for efficient multi-objective antenna optimization is presented. Our technique exploits response surface approximation (RSA) model constructed from sampled low-fidelity antenna model (here, obtained through coarse-discretization EM simulation). The RSA model enables fast determination of the best available trade-offs between conflicting design goals. A low-cost RSA model construction is possible through initial reduction of the design space. Optimization of the RSA model has been carried out using a multi-objective evolutionary algorithm (MOEA). Additional response correction techniques have been subsequently applied to improve selected designs at the high-fidelity EM antenna model level. The refined designs constitute the final Pareto set representation. The proposed approach has been validated using an ultra-wideband (UWB) monocone and a planar Yagi-Uda antenna.
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Authors (3)
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Sławomir Kozieł prof. dr inż.
- School of Science and Engineering, Reykjavik University Engineering Optimization & Modeling Center
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Leifur Leifsson
- School of Science and Engineering, Reykjavik University Engineering Optimization & Modeling Center
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- Category:
- Articles
- Type:
- artykuły w czasopismach
- Published in:
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Procedia Computer Science
no. 29,
pages 790 - 799,
ISSN: 1877-0509 - Language:
- English
- Publication year:
- 2014
- Bibliographic description:
- Bekasiewicz A., Kozieł S., Leifsson L.: Low-Cost EM-Simulation-Driven Multi-Objective Optimization of Antennas// Procedia Computer Science -Vol. 29, (2014), s.790-799
- DOI:
- Digital Object Identifier (open in new tab) 10.1016/j.procs.2014.05.071
- Verified by:
- Gdańsk University of Technology
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