Journal Article10.1007/s42835-022-01183-3
An Efficient Multi-objective Optimization Algorithm Exploiting Gradient Enhanced Kriging with Optimally Selected Basis Functions for Electromagnetic Design
TL;DR: Numerical test show that the novel multi-objective optimization strategy utilizing the gradient enhanced dynamic kriging (GEDK) method yields the same Pareto-front compared with the traditional NSGA-II method with less finite-element analysis calls.
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About: This article is published in Journal of Electrical Engineering & Technology. The article was published on 15 Aug 2022. The article focuses on the topics: Kriging & Multi-objective optimization.
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References
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TL;DR: A novel infill sampling criterion named Adaptive Multi-fidelity Expected Improvement (AMEI), in which the prediction accuracy and the optimization potential of the surrogate model are both considered, and it can be found that the AMEI always provides the best optimization result with the fewest analysis calls.
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A multiobjective proposal for the TEAM benchmark problem 22
Frederico Gadelha Guimarães,Felipe Campelo,Rodney R. Saldanha,Hajime Igarashi,Ricardo H. C. Takahashi,Jaime A. Ramírez +5 more
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Improving Adjoint-Based Aerodynamic Optimization via Gradient-Enhanced Kriging
Zhong-Hua Han
- 09 Jan 2012
TL;DR: In this article, a surrogate modeling method based on gradient-enhanced Kriging is used to determine the step size of adjoint-based optimization and a routine for adjointbased aerodynamic design has been proposed.
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