T. Simpson, J. Peplinski, P. N. Koch, and J. Allen, Metamodels for Computer-based Engineering Design: Survey and recommendations, Engineering with Computers, vol.17, issue.2, pp.129-150, 2001.
DOI : 10.1007/PL00007198

N. V. Queipo, R. T. Haftka, W. Shyy, T. Goel, R. Vaidyanathan et al., Surrogate-based analysis and optimization, Progress in Aerospace Sciences, pp.1-28, 2005.
DOI : 10.1016/j.paerosci.2005.02.001

G. G. Wang and S. Shan, Review of Metamodeling Techniques in Support of Engineering Design Optimization, Journal of Mechanical Design, vol.129, issue.4, pp.370-380, 2007.
DOI : 10.1115/1.2429697

A. I. Forrester and A. J. Keane, Recent advances in surrogate-based optimization, Progress in Aerospace Sciences, vol.45, issue.1-3, pp.50-79, 2009.
DOI : 10.1016/j.paerosci.2008.11.001
URL : https://eprints.soton.ac.uk/65935/1/Forr_09.pdf

S. Sandeep and L. , Multiobjective reliability-based and robust design optimisation for crashworthiness of a vehicle side impact, International Journal of Vehicle Design, vol.67, issue.4, pp.215-225, 2015.

A. B. Ryberg, R. D. Backryd, and L. Nilsson, A metamodel-based multidisciplinary design optimization process for automotive structures, Engineering with Computers, vol.40, issue.1???6, pp.711-728
DOI : 10.1007/s00158-009-0381-5

B. Aalae, H. Abderrahmane, and M. Gael, Computational design of an automotive twist beam, Journal of Computational Design and Engineering, vol.3, issue.3, pp.215-225, 2016.
DOI : 10.1016/j.jcde.2016.01.003

R. Su, L. Gui, and Z. Fan, Multi-objective optimization for bus body with strength and rollover safety constraints based on surrogate models. Structural and Multidisciplinary Optimization, pp.431-441, 2011.
DOI : 10.1007/s00158-011-0627-x

J. Shinkyu, O. Shigeru, and Y. Kazuomi, Aerodynamic Optimization Design with Kriging Model, TRANSACTIONS OF THE JAPAN SOCIETY FOR AERONAUTICAL AND SPACE SCIENCES, vol.48, issue.161, pp.161-168, 2005.

J. Jouhaud, P. Sagaut, M. Montagnac, and J. Laurenceau, A surrogate-model based multidisciplinary shape optimization method with application to a 2D subsonic airfoil, Computers & Fluids, vol.36, issue.3, pp.520-529, 2007.
DOI : 10.1016/j.compfluid.2006.04.001

S. Jeong, M. Murayama, and K. Yamamoto, Efficient Optimization Design Method Using Kriging Model, Journal of Aircraft, vol.2, issue.2, pp.413-419, 2005.
DOI : 10.2514/3.12533

E. Bryan, O. Zheng, N. Satish, A. F. Vladimir, and M. Igor, A methodology for meta-model based optimization in building energy models, Energy and Buildings Journal, vol.2012, issue.47, pp.292-301

A. Messac, A. Ismail-yahaya, and C. A. Mattson, The normalized normal constraint method for generating the Pareto frontier. Structural and Multidisciplinary Optimization, pp.86-98, 2003.
DOI : 10.1007/s00158-002-0276-1

A. Messac and C. Mattson, Normal Constraint Method with Guarantee of Even Representation of Complete Pareto Frontier, AIAA Journal, vol.42, issue.10, pp.2101-2111, 2004.
DOI : 10.1007/978-1-4899-3734-6_9

A. Messac and C. Mattson, Generating well-distributed sets of Pareto points for engineering design using physical programming, Optimization and Engineering, vol.3, issue.4, pp.431-450, 2002.
DOI : 10.1023/A:1021179727569

M. J. Powell, The Theory of Radial Basis Function Approximation Advances in Numerical Analysis, pp.105-210, 1992.

S. Rippa, A Radial Basis Function Method for Global Optimization, Journal of Global Optimization, vol.19, issue.3, pp.201-227, 2001.

N. Dyn, D. Levin, and S. Rippa, Numerical Procedures for Surface Fitting of Scattered Data by Radial Functions, SIAM Journal on Scientific and Statistical Computing, vol.7, issue.2, pp.639-659, 1986.
DOI : 10.1137/0907043

R. Schaback, Comparison of Radial Basis Function Interpolants, Multivariate Approximation: From CAGD to Wavelets, pp.293-305, 1993.
DOI : 10.1142/9789814503754_0018
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.50.6958

R. Duvigneau and P. Chandrashekarappa, Radial Basis Functions and Kriging Metamodels for Aerodynamic Optimization, INRIA report, pp.137602-137611, 2007.
URL : https://hal.archives-ouvertes.fr/inria-00137602

B. Aalae, Methodes efficaces de capture de front de pareto en conception mecanique multicritere : applications industrielles Nice University -Thesis, pp.33-42, 2014.

S. Rippa, An algorithm for selecting a good value for the parameter c in radial basis function interpolation, Advances in Computational Mathematics, vol.11, issue.2/3, pp.193-210, 1999.
DOI : 10.1023/A:1018975909870