Journal
IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION
Volume 62, Issue 11, Pages 5900-5905Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TAP.2014.2354673
Keywords
Antenna design; electromagnetic (EM) simulation; co-kriging; multi-objective optimization; surrogate-based optimization
Funding
- Icelandic Centre for Research (RANNIS) [130450051]
- National Science Centre of Poland [2013/11/B/ST7/04325, 2014/12/ST7/00045]
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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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