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SADEA-II: A generalized method for efficient global optimization of antenna design

SADEA-II: A generalized method for efficient global optimization of antenna design


Title: SADEA-II: A generalized method for efficient global optimization of antenna design
Author: Liu, Bo
Koziel, Slawomir   orcid.org/0000-0002-0584-4427
Ali, Nazar
Date: 2016-11-20
Language: English
Scope: 86-97
University/Institute: Háskólinn í Reykjavík
Reykjavik University
School: Tækni- og verkfræðideild (HR)
School of Science and Engineering (RU)
Series: Journal of Computational Design and Engineering;4(2)
ISSN: 2288-4300
2288-5048 (eISSN)
DOI: 10.1016/j.jcde.2016.11.002
Subject: Antenna design optimization; Antenna design automation; Surrogate-model-assisted evolutionary algorithm; Expensive optimization; Multi-fidelity; Variable fidelity; Gaussian process; Loftnet; Hönnun; Bestun; Líkön; Hermilíkön; Reiknirit; Slembiferli
URI: https://hdl.handle.net/20.500.11815/1662

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Citation:

Liu, B., Koziel, S., & Ali, N. (2017). SADEA-II: A generalized method for efficient global optimization of antenna design. Journal of Computational Design and Engineering, 4(2), 86–97. https://doi.org/10.1016/j.jcde.2016.11.002

Abstract:

Efficiency improvement is of great significance for simulation-driven antenna design optimization methods based on evolutionary algorithms (EAs). The two main efficiency enhancement methods exploit data-driven surrogate models and/or multi-fidelity simulation models to assist EAs. However, optimization methods based on the latter either need ad hoc low-fidelity model setup or have difficulties in handling problems with more than a few design variables, which is a main barrier for industrial applications. To address this issue, a generalized three stage multi-fidelity simulation -model assisted antenna design optimization framework is proposed in this paper. The main ideas include introduction of a novel data mining stage handling the discrepancy between simulation models of different fidelities, and a surrogate-model-assisted combined global and local search stage for efficient high-fidelity simulation model-based optimization. This framework is then applied to SADEA, which is a state-ofthe-art surrogate-model-assisted antenna design optimization method, constructing SADEA-II. Experimental results indicate that SADEA-II successfully handles various discrepancy between simulation models and considerably outperforms SADEA in terms of computational efficiency while ensuring improved design quality.

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This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

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