Title: | SADEA-II: A generalized method for efficient global optimization of antenna design |
Author: |
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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) |
Department: | Engineering Optimization & Modeling Center (EOMC) (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 |
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
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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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Rights: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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