Háskólinn í ReykjavíkReykjavik UniversityLiu, BoKoziel, SlawomirAli, Nazar2020-03-272020-03-272016-11-20Liu, 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.2016.11.0022288-43002288-5048 (eISSN)https://hdl.handle.net/20.500.11815/1662Efficiency 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.86-97eninfo:eu-repo/semantics/openAccessAntenna design optimizationAntenna design automationSurrogate-model-assisted evolutionary algorithmExpensive optimizationMulti-fidelityVariable fidelityGaussian processLoftnetHönnunBestunLíkönHermilíkönReikniritSlembiferliSADEA-II: A generalized method for efficient global optimization of antenna designinfo:eu-repo/semantics/articleJournal of Computational Design and Engineering10.1016/j.jcde.2016.11.002