**Author details**

Shima Rahmani<sup>1</sup> , Elyas Fadakar<sup>2</sup> and Masoud Ebrahimi<sup>3</sup> \*

1 School of Computer Science and Statistics, Trinity College Dublin, Dublin, Ireland

2 Electronics and Information Engineering, Beihang University (BUAA), Beijing, China

3 Faculty of Mechanical Engineering, Tarbiat Modares University, Tehran, Iran

\*Address all correspondence to: ebrahimikm@modares.ac.ir

© 2023 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

*An Efficient Quantile-Based Adaptive Sampling RBDO with Shifting Constraint Strategy DOI: http://dx.doi.org/10.5772/intechopen.110442*
