Abstract
A novel formulation for design under uncertainty is presented, which is based on the computation of the mean value and the minimum of the function. The aim of the method is to exert a stronger control on the system output variability in the optimization loop at a moderate cost. This would reduce post-processing analysis of the PDF of the resulting optimal designs, by converging rapidly to the interesting individuals. In other words, in the set of designs resulting from the optimization, the new approach should be capable of discarding poor-performance design. Also, no a priori assumption of optimal PDF is made. The preliminary results presented in the paper proves the benefit of the new formulation.
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The authors acknowledge the associated team (Inria-UQ Lab Stanford) AQUARIUS for the financial support.
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Fusi, F., Congedo, P.M., Geraci, G., Iaccarino, G. (2019). An Alternative Formulation for Design Under Uncertainty. In: Minisci, E., Vasile, M., Periaux, J., Gauger, N., Giannakoglou, K., Quagliarella, D. (eds) Advances in Evolutionary and Deterministic Methods for Design, Optimization and Control in Engineering and Sciences. Computational Methods in Applied Sciences, vol 48. Springer, Cham. https://doi.org/10.1007/978-3-319-89988-6_24
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DOI: https://doi.org/10.1007/978-3-319-89988-6_24
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