dc.contributor |
Háskólinn í Reykjavík |
dc.contributor |
Reykjavik University |
dc.contributor.author |
Liu, Bo |
dc.contributor.author |
Koziel, Slawomir |
dc.contributor.author |
Ali, Nazar |
dc.date.accessioned |
2020-03-27T10:41:59Z |
dc.date.available |
2020-03-27T10:41:59Z |
dc.date.issued |
2016-11-20 |
dc.identifier.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 |
dc.identifier.issn |
2288-4300 |
dc.identifier.issn |
2288-5048 (eISSN) |
dc.identifier.uri |
https://hdl.handle.net/20.500.11815/1662 |
dc.description.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. |
dc.description.sponsorship |
The authors thank CST AG for making CST Microwave Studio available. The authors would like to thank Dr. Renato Cordeiro de Amorim, Glyndwr University, UK for valuable discussions. |
dc.format.extent |
86-97 |
dc.language.iso |
en |
dc.publisher |
Oxford University Press (OUP) |
dc.relation.ispartofseries |
Journal of Computational Design and Engineering;4(2) |
dc.rights |
info:eu-repo/semantics/openAccess |
dc.subject |
Antenna design optimization |
dc.subject |
Antenna design automation |
dc.subject |
Surrogate-model-assisted evolutionary algorithm |
dc.subject |
Expensive optimization |
dc.subject |
Multi-fidelity |
dc.subject |
Variable fidelity |
dc.subject |
Gaussian process |
dc.subject |
Loftnet |
dc.subject |
Hönnun |
dc.subject |
Bestun |
dc.subject |
Líkön |
dc.subject |
Hermilíkön |
dc.subject |
Reiknirit |
dc.subject |
Slembiferli |
dc.title |
SADEA-II: A generalized method for efficient global optimization of antenna design |
dc.type |
info:eu-repo/semantics/article |
dcterms.license |
This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/) |
dc.description.version |
"Peer Reviewed" |
dc.identifier.journal |
Journal of Computational Design and Engineering |
dc.identifier.doi |
10.1016/j.jcde.2016.11.002 |
dc.contributor.department |
Engineering Optimization & Modeling Center (EOMC) (RU) |
dc.contributor.school |
Tækni- og verkfræðideild (HR) |
dc.contributor.school |
School of Science and Engineering (RU) |