Abstract
One of the most important tools of antenna design is electromagnetic (EM) simulation. High-fidelity simulations offer accurate evaluation of the antenna performance, however, they are computationally expensive. As a result, employing EM solvers in automated antenna design using numerical optimization techniques is quite challenging. A possible workaround are surrogate-based optimization (SBO) methods. In case of antennas, the generic way to construct the surrogate is through coarse-discretization EM simulations that are faster but, at the same time, less accurate. For most SBO algorithms, quality of such low-fidelity models may be critical for performance. In this work, we investigate the trade-offs between the speed and the accuracy of the low-fidelity antenna models as well as the impact of the model selection on the quality of the design produced by the SBO algorithm as well as the computational cost of the optimization process. Our considerations are illustrated using examples.
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Koziel, S., Ogurtsov, S., Leifsson, L. (2014). On Low-Fidelity Model Selection for Antenna Design Using Variable-Resolution EM Simulations. In: Obaidat, M., Filipe, J., Kacprzyk, J., Pina, N. (eds) Simulation and Modeling Methodologies, Technologies and Applications. Advances in Intelligent Systems and Computing, vol 256. Springer, Cham. https://doi.org/10.1007/978-3-319-03581-9_19
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DOI: https://doi.org/10.1007/978-3-319-03581-9_19
Publisher Name: Springer, Cham
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