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Design space reduction and variable-fidelity EM simulations for feasible Pareto optimization of antennas
Abstract
A computationally efficient procedure for multi-objective optimization of antenna structures is presented. In our approach, a response surface approximation (RSA) model created from sampled coarse-discretization EM antenna simulations is utilized to yield an initial set of Pareto-optimal designs using a multi-objective evolutionary algorithm. The final Pareto front representation for the high-fidelity model is obtained using surrogate-based optimization techniques. A critical stage of the design process is an initial reduction of the design space aimed at estimating the region containing the Pareto set, which allows for low-cost construction of the RSA model even if the number of designable parameters is large. Illustration example is provided. An importance of the design space reduction is also demonstrated.
Authors (3)
-
Sławomir Kozieł prof. dr inż.
- School of Science and Engineering, Reykjavik University Engineering Optimization & Modeling Center
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- Category:
- Conference activity
- Type:
- publikacja w wydawnictwie zbiorowym recenzowanym (także w materiałach konferencyjnych)
- Title of issue:
- The 30th International Review of Progress in Applied Computational Electromagnetics strony 1 - 6
- Language:
- English
- Publication year:
- 2014
- Bibliographic description:
- Bekasiewicz A., Koziel S., Zieniutycz W.: Design space reduction and variable-fidelity EM simulations for feasible Pareto optimization of antennas// The 30th International Review of Progress in Applied Computational Electromagnetics/ : , 2014, s.1-6
- Verified by:
- Gdańsk University of Technology
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