T. J. Santner, B. J. Williams, and W. Notz, The Design and Analysis of Computer Experiments, 2003.
DOI : 10.1007/978-1-4757-3799-8

D. R. Jones, A taxonomy of global optimization methods based on response surfaces, Journal of Global Optimization, vol.21, issue.4, pp.345-383, 2001.
DOI : 10.1023/A:1012771025575

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

T. W. Simpson, J. D. Poplinski, P. N. Koch, and J. K. 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

M. D. Mckay, R. J. Beckman, and W. J. Conover, A comparison of three methods for selecting values of input variables in the analysis of output from a computer code, Technometrics, vol.21, issue.2, pp.239-245, 1979.

G. Matheron, Principles of geostatistics, Economic Geology, vol.58, issue.8, pp.1246-1266, 1963.
DOI : 10.2113/gsecongeo.58.8.1246

C. E. Rasmussen and C. K. Williams, Gaussian Processes in Machine Learning, 2006.
DOI : 10.1162/089976602317250933

D. R. Jones, M. J. 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.
DOI : 10.1023/A:1008306431147

A. I. Forrester, A. Sobester, and A. J. Keane, Engineering Design via Surrogate Modelling: a Practical Guide, 2008.
DOI : 10.1002/9780470770801

D. Huang, T. T. Allen, W. I. Notz, and N. Zeng, Global Optimization of Stochastic Black-Box Systems via Sequential Kriging Meta-Models, Journal of Global Optimization, vol.25, issue.1, pp.441-466, 2006.
DOI : 10.1007/s10898-005-2454-3

M. J. Sasena, Flexibility and Efficiency Enhancements for Constrained Global Design Optimization with Kriging Approximations, 2002.

J. Villemonteix, E. Vazquez, and E. Walter, An informational approach to the global optimization of expensive-to-evaluate functions, Journal of Global Optimization, vol.10, issue.5, pp.509-534, 2009.
DOI : 10.1007/s10898-008-9354-2
URL : https://hal.archives-ouvertes.fr/hal-00354262

E. Vazquez and J. Bect, Convergence properties of the expected improvement algorithm with fixed mean and covariance functions, Journal of Statistical Planning and Inference, vol.140, issue.11, pp.3088-3095, 2010.
DOI : 10.1016/j.jspi.2010.04.018
URL : https://hal.archives-ouvertes.fr/hal-00217562

D. Huang and T. T. Allen, Design and analysis of variable fidelity experimentation applied to engine valve heat treatment process design, Journal of the Royal Statistical Society: Series C (Applied Statistics), vol.4, issue.2, pp.443-463, 2005.
DOI : 10.1007/s00158-002-0195-1

J. Villemonteix, E. Vazquez, and E. Walter, Bayesian optimization for parameter identification on a small simulation budget, Proceedings of the 15th IFAC Symposium on System Identification, 2009.
DOI : 10.3182/20090706-3-FR-2004.00266
URL : https://hal.archives-ouvertes.fr/hal-00368152

J. Marzat, E. Walter, H. Piet-lahanier, and F. Damongeot, Automatic tuning via Krigingbased optimization of methods for fault detection and isolation, Proceedings of the IEEE Conference on Control and Fault-Tolerant Systems, pp.505-510, 2010.
URL : https://hal.archives-ouvertes.fr/hal-00520808

J. Defretin, J. Marzat, and H. Piet-lahanier, Learning Viewpoint Planning in Active Recognition on a Small Sampling Budget: A Kriging Approach, 2010 Ninth International Conference on Machine Learning and Applications, pp.169-174, 2010.
DOI : 10.1109/ICMLA.2010.32
URL : https://hal.archives-ouvertes.fr/hal-00520814

H. G. Beyer and B. Sendhoff, Robust optimization ??? A comprehensive survey, Computer Methods in Applied Mechanics and Engineering, vol.196, issue.33-34, pp.33-343190, 2007.
DOI : 10.1016/j.cma.2007.03.003

G. Dellino, J. P. Kleijnen, and C. Meloni, Robust optimization in simulation: Taguchi and Response Surface Methodology, International Journal of Production Economics, vol.125, issue.1, pp.52-59, 2010.
DOI : 10.1016/j.ijpe.2009.12.003

W. Chen, J. K. Allen, K. L. Tsui, and F. Mistree, A Procedure for Robust Design: Minimizing Variations Caused by Noise Factors and Control Factors, Journal of Mechanical Design, vol.118, issue.4, pp.478-485, 1996.
DOI : 10.1115/1.2826915

K. Lee, G. Park, and W. Joo, A Global Robust Optimization Using Kriging Based Approximation Model, Proceedings of the 6th World Congresses of Structural and Multidisciplinary Optimization, 2005.
DOI : 10.1299/jsmec.49.779

B. J. Williams, T. J. Santner, and W. I. Notz, Sequential design of computer experiments to minimize integrated response functions, Statistica Sinica, vol.10, issue.4, pp.1133-1152, 2000.

J. S. Lehman, T. J. Santner, and W. I. Notz, Designing computer experiments to determine robust control variables, Statistica Sinica, vol.14, issue.2, pp.571-590, 2004.

C. Q. Lam, Sequential Adaptive Designs in Computer Experiments for Response Surface Model Fit, 2008.

A. M. Cramer, S. D. Sudhoff, and E. L. Zivi, Evolutionary Algorithms for Minimax Problems in Robust Design, IEEE Transactions on Evolutionary Computation, vol.13, issue.2, pp.444-453, 2009.
DOI : 10.1109/TEVC.2008.2004422

R. I. Lung and D. Dumitrescu, A new evolutionary approach to minimax problems, 2011 IEEE Congress of Evolutionary Computation (CEC), pp.1902-1905, 2011.
DOI : 10.1109/CEC.2011.5949847

A. Zhou and Q. Zhang, A surrogate-assisted evolutionary algorithm for minimax optimization, IEEE Congress on Evolutionary Computation, pp.1-7, 2010.
DOI : 10.1109/CEC.2010.5586122

K. Shimizu and E. Aiyoshi, Necessary conditions for min-max problems and algorithms by a relaxation procedure, IEEE Transactions on Automatic Control, vol.25, issue.1, pp.62-66, 1980.
DOI : 10.1109/TAC.1980.1102226

B. Rustem and M. Howe, Algorithms for Worst-Case Design and Applications to Risk Management, 2002.
DOI : 10.1515/9781400825110

B. Brown and T. Singh, Minimax design of vibration absorbers for linear damped systems, Journal of Sound and Vibration, vol.330, issue.11, pp.2437-2448, 2011.
DOI : 10.1016/j.jsv.2010.12.002

D. M. Salmon, Minimax controller design, IEEE Transactions on Automatic Control, vol.13, issue.4, pp.369-376, 1968.
DOI : 10.1109/TAC.1968.1098941

J. Helton, Worst case analysis in the frequency domain: The H^???approach to control, IEEE Transactions on Automatic Control, vol.30, issue.12, pp.1154-1170, 1985.
DOI : 10.1109/TAC.1985.1103860

E. Y. Chow and A. S. Willsky, Analytical redundancy and the design of robust failure detection systems, IEEE Transactions on Automatic Control, vol.29, issue.7, pp.603-614, 1984.
DOI : 10.1109/TAC.1984.1103593

P. M. Frank and X. Ding, Survey of robust residual generation and evaluation methods in observer-based fault detection systems, Journal of Process Control, vol.7, issue.6, pp.403-424, 1997.
DOI : 10.1016/S0959-1524(97)00016-4

B. Colson, P. Marcotte, and G. Savard, An overview of bilevel optimization, Annals of Operations Research, vol.89, issue.1, pp.235-256, 2007.
DOI : 10.1007/s10479-007-0176-2

A. Ben-tal and A. Nemirovski, Robust Convex Optimization, Mathematics of Operations Research, vol.23, issue.4, pp.769-805, 1998.
DOI : 10.1287/moor.23.4.769

T. Ba¸sarba¸sar and G. J. Olsder, Dynamic Noncooperative Game Theory, Society for Industrial Mathematics, 1999.

D. Du and P. M. Pardalos, Minimax and Applications, 1995.
DOI : 10.1007/978-1-4613-3557-3

P. Parpas and B. Rustem, An Algorithm for the Global Optimization of a Class of??Continuous Minimax Problems, Journal of Optimization Theory and Applications, vol.15, issue.3, pp.461-473, 2009.
DOI : 10.1007/s10957-008-9473-4

A. Tsoukalas, B. Rustem, and E. N. Pistikopoulos, A global optimization algorithm for generalized semi-infinite, continuous minimax with coupled constraints and bi-level problems, Journal of Global Optimization, vol.36, issue.2, pp.235-250, 2009.
DOI : 10.1007/s10898-008-9321-y

B. Rustem, Algorithms for Nonlinear Programming and Multiple Objective Decisions, 1998.

K. Shimizu, Y. Ishizuka, and J. F. Bard, Nondifferentiable and Two-level Mathematical Programming, 1997.
DOI : 10.1007/978-1-4615-6305-1

D. J. Mackay, Information Theory, Inference, and Learning Algorithms, 2003.

M. Schonlau, Computer Experiments and Global Optimization, 1997.

D. R. Jones, C. D. Perttunen, and B. E. Stuckman, Lipschitzian optimization without the Lipschitz constant, Journal of Optimization Theory and Applications, vol.20, issue.1, pp.157-181, 1993.
DOI : 10.1007/BF00941892

M. Basseville and I. V. Nikiforov, Detection of Abrupt Changes: Theory and Application, 1993.
URL : https://hal.archives-ouvertes.fr/hal-00008518

M. Barty´sbarty´s, R. J. Patton, M. Syfert, S. De, J. Heras et al., Introduction to the DAMADICS actuator FDI benchmark study, Control Engineering Practice, vol.14, issue.6, pp.577-596, 2006.
DOI : 10.1016/j.conengprac.2005.06.015