D. R. Jones, M. Schonlau, and W. J. Welch, Efficient Global Optimization of Expensive Black-Box Functions, Journal of Global Optimization, vol.13, issue.4, pp.455-492, 1998.

A. Forrester, A. Sobester, and A. Keane, Engineering design via surrogate modelling: a practical guide, 2008.

M. J. Sasena, Flexibility and efficiency enhancements for constrained global design optimization with kriging approximations, 2002.

R. S. Sellar, S. M. Batill, R. , and J. E. , Response Surface Based, Concurrent Subspace Optimization For Multidisciplinary System Design, 34th AIAA Aerospace Sciences Meeting and Exhibit, vol.5, pp.96-0714, 1996.

P. D. Ciampa and B. Nagel, Towards the 3rd generation MDO collaboration Environment, 2016.

I. R. Chittick and J. R. Martins, An asymmetric suboptimization approach to aerostructural optimization, Optimization and Engineering, vol.10, issue.1, pp.133-152, 2008.

C. E. Rasmussen and C. K. Williams, Gaussian processes for machine learning, Adaptive computation and machine learning, 2006.

M. Arnst, R. Ghanem, E. Phipps, and J. Red-horse, Dimension reduction in stochastic modeling of coupled problems, International Journal for Numerical Methods in Engineering, vol.92, issue.11, pp.940-968, 2012.

S. Sankararaman and S. Mahadevan, Likelihood-Based Approach to Multidisciplinary Analysis Under Uncertainty, Journal of Mechanical Design, vol.134, issue.3, pp.31008-31020, 2012.

S. Dubreuil, N. Bartoli, C. Gogu, and T. Lefebvre, Propagation of Modeling uncertainty by Polynomial Chaos Expansion in Muldisciplinary Analysis, Journal of Mechanical Design, vol.138, issue.11, p.111411, 2016.

R. H. Cameron and W. T. Martin, The Orthogonal Development of Non-Linear Functionals in Series of Fourier-Hermite Functionals, Annals of Mathematics, vol.48, issue.2, pp.385-392, 1947.

R. G. Ghanem and P. D. Spanos, Stochastic finite elements: a spectral approach, 1991.

M. Berveiller, B. Sudret, and M. Lemaire, Stochastic finite elements: a non-intrusive approach by regression, European Journal of Computational Mechanics, vol.15, issue.1, pp.81-92, 2006.

S. Dubreuil, N. Bartoli, C. Gogu, T. Lefebvre, and J. M. Colomer, Extreme value oriented random field discretization based on an hybrid polynomial chaos expansion-Kriging approach, Computer Methods in Applied Mechanics and Engineering, 2018.
URL : https://hal.archives-ouvertes.fr/hal-01712026

D. Kraft, A software package for sequential quadratic programming, DFVLR Obersfaffeuhofen, 1988.

M. J. Powell, An efficient method for finding the minimum of a function of several variables without calculating derivatives, The Computer Journal, vol.7, issue.2, pp.155-162, 1964.

P. D. Ciampa and B. Nagel, The AGILE Paradigm: the next generation of collaborative MDO, 18th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, 2017.

T. Lefebvre, N. Bartoli, S. Dubreuil, M. Panzeri, R. Lombardi et al., Overview Of MDO Enhancement In The AGILE Project: A Clustered And Surrogate-Based MDA Use Case, 6th CEAS Aerospace Europe Conference, 2017.