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Abstract
A surrogate-based technique for fast multi-objective optimization of a multi-parameter planar Yagi-Uda antenna structure is presented. The proposed method utilizes response surface approximation (RSA) models constructed using training samples obtained from evaluation of the low-fidelity antenna model. Utilization of the RSA models allowsfor fast determination of the best possible trade-offs between conflicting objectives in multi-objective optimization framework. Computationally feasible construction of the RSA model for the multi-parameter case is possible by initial reduction of the antenna solution space. The initial set of Pareto-optimal designs is obtained by optimizing the model with a multi-objective evolutionary algorithm (MOEA). Surrogate-based optimization is subsequently carried out to elevate the selected designs to the high-fidelity antenna model level. The refined Pareto optimal-set for the considered Yagi-Uda antenna is generated atthe low computational cost corresponding to about 194 high-fidelity EM antenna simulations
Authors (3)
-
Sławomir Kozieł prof. dr inż.
- School of Science and Engineering, Reykjavik University Engineering Optimization & Modeling Center
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Details
- Category:
- Conference activity
- Type:
- materiały konferencyjne indeksowane w Web of Science
- Title of issue:
- International Conference on Microwave Radar and Wireless Communications strony 1 - 4
- Language:
- English
- Publication year:
- 2014
- Bibliographic description:
- Bekasiewicz A., Kozieł S., Zieniutycz W..: Low-Cost Multi-Objective Optimization Yagi-Uda Antenna in Multi-Dimensional Parameter Space, W: International Conference on Microwave Radar and Wireless Communications, 2014, ,.
- Verified by:
- Gdańsk University of Technology
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