In this paper, we propose an evolutionary framework for model fidelity control that decides, at runtime, the appropriate fidelity level of the computational model, which is deemed to be computationally less expensive, to be used in place of the exact analysis code as the search progresses. Empirical study on an aerodynamic airfoil design problem based on a Memetic Algorithm with Dynamic Fidelity Model (MA-DFM) demonstrates that improved quality solution and efficiency are obtained over existing evolutionary schemes. © 2008 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Lim, D., Ong, Y. S., Jin, Y., & Sendhoff, B. (2008). Evolutionary optimization with dynamic fidelity computational models. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5227 LNAI, pp. 235–242). https://doi.org/10.1007/978-3-540-85984-0_29
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