C. Audet and J. E. Dennis, Analysis of Generalized Pattern Searches, SIAM Journal on Optimization, vol.13, issue.3, pp.889-903, 2003.
DOI : 10.1137/S1052623400378742

A. R. Conn, K. Scheinberg, and L. N. Vicente, Global Convergence of General Derivative-Free Trust-Region Algorithms to First- and Second-Order Critical Points, SIAM Journal on Optimization, vol.20, issue.1, 2009.
DOI : 10.1137/060673424

A. R. Conn, K. Scheinberg, and L. N. Vicente, Introduction to Derivative-Free Optimization, Society for Industrial and Applied MathematicsMPS-SIAM Series on Optimization), 2009.
DOI : 10.1137/1.9780898718768

H. M. Gutmann, Radial Basis Function Methods for Global Optimization, 2001.

N. Hansen and A. Ostermeier, Adapting arbitrary normal mutation distributions in evolution strategies: the covariance matrix adaptation, Proceedings of IEEE International Conference on Evolutionary Computation, pp.312-317, 1996.
DOI : 10.1109/ICEC.1996.542381

D. Jones, Large-scale multi-disciplinary mass optimization in the auto industry, 2008.

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

C. T. Kelley, Iterative methods for optimization, 1999.
DOI : 10.1137/1.9781611970920

S. Kirkpatrick, C. D. Gelatt, and M. P. Vecchi, Optimization by Simulated Annealing, Science, vol.220, issue.4598, pp.671-680, 1983.
DOI : 10.1126/science.220.4598.671

T. G. Kolda, R. M. Lewis, and V. Torczon, Optimization by Direct Search: New Perspectives on Some Classical and Modern Methods, SIAM Review, vol.45, issue.3, pp.385-482, 2003.
DOI : 10.1137/S003614450242889

H. Langouët and D. Sinoquet, Derivative free optimization under constraints, ENBIS EMSE, pp.1-3, 2009.

M. Marazzi and J. Nocedal, Wedge trust region methods for derivative free optimization, Mathematical Programming, vol.91, issue.2, pp.289-305, 2002.
DOI : 10.1007/s101070100264

N. Metla, F. Delbos, S. Da-veiga, and D. Sinoquet, Constrained Nonlinear Optimization for Extreme Scenarii Evaluation in Reservoir Characterization, 12th European Conference on the Mathematics of Oil Recovery, pp.6-9, 2010.
DOI : 10.3997/2214-4609.20145035

J. J. Moré and S. M. Wild, Benchmarking Derivative-Free Optimization Algorithms, SIAM Journal on Optimization, vol.20, issue.1, pp.172-191, 2009.
DOI : 10.1137/080724083

J. A. Nelder and R. Mead, A Simplex Method for Function Minimization, The Computer Journal, vol.7, issue.4, pp.308-313, 1965.
DOI : 10.1093/comjnl/7.4.308

M. J. Powell, The NEWUOA software for unconstrained optimization without derivatives, Tech. rep., Department of Applied Mathematics and Theoretical Physics, 2006.
DOI : 10.1007/0-387-30065-1_16

M. J. Powell, Developments of newuoa for unconstrained minimization without derivatives, 2007.

R. G. Regis, Radial basis function algorithms for large-scale nonlinearly constrained black-box optimization, 20th International Symposium on Mathematical Programming Chicago, IL, pp.113-135, 2009.

R. G. Regis and C. A. Shoemaker, Improved Strategies for Radial basis Function Methods for Global Optimization, Journal of Global Optimization, vol.90, issue.1, pp.113-135, 2007.
DOI : 10.1007/s10898-006-9040-1

. Roggero, Constraining stochastic reservoir models to dynamic data: an integrated approach, 2001.

F. Roggero, Constraining reservoir models to production and 4d seismic data -application to the girassol field, 2008.

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

D. Sinoquet and F. Delbos, Adapted Nonlinear Optimization Method for Production Data and 4D Seismic Inversion, 11th European Conference on the Mathematics of Oil Recovery, pp.8-11, 2008.
DOI : 10.3997/2214-4609.20146436

F. Vanden-berghen, CONDOR: a constrained, non-linear, derivative-free parallel optimizer for continuous , high computing load, noisy objective functions, 2004.

J. Villemonteix, Optimisation De Fonctions Coûteuses: Modèles Gaussiens Pour Une Utilisation Efficace Du Budget D'´ evaluations : Théorie Et Pratique Industrielle, 2008.

T. A. Winslow, R. J. Trew, P. Gilmore, and C. T. Kelley, Doping profiles for optimum class B performance of GaAs MESFET amplifiers, [1991] Proceedings IEEE/Cornell Conference on Advanced Concepts in High Speed Semiconductor Devices and Circuits, pp.188-197, 1991.
DOI : 10.1109/CORNEL.1991.170048

H. Zhang, A. R. Conn, and K. Scheinberg, A Derivative-Free Algorithm for Least-Squares Minimization, SIAM Journal on Optimization, vol.20, issue.6, 2009.
DOI : 10.1137/09075531X

M. Castagné, Y. Bentolila, A. Hallé, F. Nicolas, and D. Sinoquet, Engine calibration : towards an integrated approach, DoE in engine development IV, 2007.

H. Langouët, F. Delbos, D. Sinoquet, S. Da, and . Veiga, A Derivative Free Optimization Method for Reservoir Characterization Inverse Problem, 12th European Conference on the Mathematics of Oil Recovery, pp.6-9, 2010.
DOI : 10.3997/2214-4609.20144992

S. Magand, B. Lecointe, F. Chaudoye, and M. Castagné, Optimization of a Euro 5 Vehicle Powered by an Ethanol Based Diesel Fuel, SAE International Journal of Fuels and Lubricants, vol.3, issue.2, 2010.
DOI : 10.4271/2010-01-1520

F. Chaudoye, M. Castagné, B. Lecointe, and S. Magand, Advanced calibration methods applied with an innovative ethanol/diesel fuel formulation, 2010.

M. Castagné, Y. Bentolila, F. Chaudoye, A. Hallé, F. Nicolas et al., Comparison of engine calibration methods based on DoE, Oil and Gas Science and Technology 63, pp.563-582, 2008.

F. Chaudoye, M. Castagné, D. Sinoquet, and F. Wahl, Modelling engine operating space for DoE calibration methods, IAV Conference, 2009.

A. Albrecht, O. Grondin, F. L. Berr, and G. L. Solliec, Towards a Stronger Simulation Support for Engine Control Design: a Methodological Point of View, Oil & Gas Science and Technology - Revue de l'IFP, vol.62, issue.4, 2007.
DOI : 10.2516/ogst:2007039

F. Lafossas, M. Marbaix, and P. Menegazzi, Development and Application of a 0D D.I. Diesel combustion model for Emissions Prediction, SAE Technical Paper Series, 1841.
DOI : 10.4271/2007-01-1841

C. Barba, C. Burkhardt, K. Boulouchos, and M. Bargende, A Phenomenological Combustion Model for Heat Release Rate Prediction in High-Speed DI Diesel Engines with Common Rail Injection, SAE Technical Paper Series, 2000.
DOI : 10.4271/2000-01-2933

R. Lebas, G. Mauviot, F. L. Berr, and A. Albrecht, A Phenomenological Approach to Model Diesel Engine Combustion and In-Cylinder Pollutant Emissions Adapted to Control Strategy, IFAC Paper, p.9, 2009.

G. Woschni, A Universally Applicable Equation for the Instantaneous Heat Transfer Coefficient in the Internal Combustion Engine, SAE Technical Paper Series, 1967.
DOI : 10.4271/670931

D. Sinoquet, H. Langouët, F. Chaudoye, and M. Castagné, Multi-objective constrained optimization of engine maps, 5th IAV conference: Design of Experiments (DoE) in Engine Development, 2009.

M. J. Powell, The NEWUOA software for unconstrained optimization without derivatives, Tech. rep., Department of Applied Mathematics and Theo- retical Physics, Centre for Mathematical Sciences, 2006.

M. B. Gaid, G. Corde, A. Chasse, B. Léty, R. De-la-rubia et al., Heterogeneous Model Integration and Virtual Experimentation Using xMOD: Application to Hybrid Powertrain Design and Validation. EUROSIM'10, 2010.
URL : https://hal.archives-ouvertes.fr/hal-00911776

. Probl-`-emesprobl-`-probl-`-emes-lisses-1 and B. Probl-`-emesprobl-`-probl-`-emes-lisses-akteke, Derivative free optimization methods : Application in stirrer configuration and data clustering, MIDDLE EAST TECHNICAL UNI- VERSITY, 2005.

N. M. Alexandrov, J. E. Dennis, R. M. Lewis, and V. Torczon, A trust-region framework for managing the use of approximation models in optimization, Structural Optimization, vol.12, issue.1, pp.16-23, 1998.
DOI : 10.1007/BF01197433

C. Audet, D. , and J. , Analysis of Generalized Pattern Searches, SIAM Journal on Optimization, vol.13, issue.3, pp.889-903, 2003.
DOI : 10.1137/S1052623400378742

A. Auger, N. Hansen, J. M. Perez-zerpa, R. Ros, and M. Schoenauer, Empirical comparisons of several derivative free optimization algorithms
URL : https://hal.archives-ouvertes.fr/hal-01408402

A. Auger, N. Hansen, J. M. Perez-zerpa, R. Ros, and M. Schoenauer, Experimental Comparisons of Derivative Free Optimization Algorithms, 8th International Symposium on Experimental Algorithms, 2009.
DOI : 10.1007/978-3-642-02011-7_3

URL : https://hal.archives-ouvertes.fr/inria-00397334

M. H. Bakr, J. W. Bandler, K. Madsen, and J. Sondergaard, Review of the space mapping approach to engineering optimization and modeling, Optimization and Engineering, vol.1, pp.3-241, 2000.

J. W. Bandler, R. M. Biernacki, S. H. Chen, P. A. Grobelny, and R. H. Hemmers, Space mapping technique for electromagnetic optimization, IEEE Transactions on Microwave Theory and Techniques, vol.42, issue.12, pp.42-2536, 1994.
DOI : 10.1109/22.339794

J. W. Bandler, Q. S. Cheng, S. Dakroury, A. S. Mohamed, M. H. Bakr et al., Space Mapping: The State of the Art, IEEE Transactions on Microwave Theory and Techniques, vol.52, issue.1, pp.337-361, 2004.
DOI : 10.1109/TMTT.2003.820904

V. Barichard, Approches Hybrides Pour LesProbì emes multiobjectifs, 2003.

M. Basseur, Design of cooperative metaheuristics for multiobjective optimization : Application to the FlowShop scheduling Problem, 2005.

A. Berro, Optimisation Multiobjectif et Stratégies d'Evolution en Environnement Dynamique, 2001.

R. Bettinger, Inversion d'un système par krigeage appliquéè a la synthèse de catalyseursàcatalyseursà haut débit, 2009.

R. Bettinger, P. Duchene, L. Pronzato, and E. Thierry, Design of experiments for response diversity, Journal of Physics : Conference Series Proc. 6th International Conference on Inverse Problems in Engineering (ICIPE), 2008.
DOI : 10.1088/1742-6596/135/1/012017

URL : https://hal.archives-ouvertes.fr/hal-00290418

H. Beyer and H. Schwefel, Evolution strategies, Scholarpedia, vol.2, issue.8, pp.3-52, 2002.
DOI : 10.4249/scholarpedia.1965

G. Bilchev and P. , The ant colony metaphor for searching continuous design spaces, Lecture Notes in Computer Science, vol.993, pp.25-39, 1995.
DOI : 10.1007/3-540-60469-3_22

M. Björkman and K. Holmström, Global optimization of costly nonconvex functions using radial basis functions, Optimization and Engineering, vol.1, issue.4, pp.373-397, 2000.
DOI : 10.1023/A:1011584207202

J. F. Bonnans, J. C. Gilbert, C. Lemarechal, and C. A. Sagastizabal, Numerical Optimization : Theoretical And Practical Aspects, 2003.
DOI : 10.1007/978-3-662-05078-1

A. J. Booker, J. E. Dennis, J. Frank, P. D. Serafini, D. B. Torczon et al., A rigorous framework for optimization of expensive functions by surrogates, Structural Optimization, vol.16, issue.1, pp.98-145, 1998.
DOI : 10.1007/BF01197708

Z. Bouzarkouna, D. Ding, and A. Auger, Using Evolution Strategy with Meta-models for Well Placement Optimization, 12th European Conference on the Mathematics of Oil Recovery, p.2010, 2010.
DOI : 10.3997/2214-4609.20144991

URL : https://hal.archives-ouvertes.fr/inria-00538745

G. E. Box, Evolutionary Operation: A Method for Increasing Industrial Productivity, Applied Statistics, vol.6, issue.2, pp.81-101, 1957.
DOI : 10.2307/2985505

G. E. Box, W. , and K. B. , On the Experimental Attainment of Optimum Conditions, Roy. Statist. Soc. Ser. B, vol.13, pp.1-45, 1951.
DOI : 10.1007/978-1-4612-4380-9_23

M. Casse, Sparse Grid : de l'approximation des EDP au calcul de sensibilité, 2010.

M. Castagné, Y. Bentolila, F. Chaudoye, A. Hallé, F. Nicolas et al., Comparison of Engine Calibration Methods Based on Design of Experiments (DoE), Oil & Gas Science and Technology - Revue de l'IFP, vol.63, issue.4, pp.563-582, 2008.
DOI : 10.2516/ogst:2008029

F. Chaudroye, M. Castagne, D. Sinoquet, and F. Wahl, Modelling engine operating space for doe calibration methods, 5th Conference Design fo Experiments (DoE) in Engine Development, pp.26-2009, 2009.

A. Colorni, M. Dorigo, and V. Maniezzo, Distributed optimization by ant colonies. actes de lapremì ere conférence européenne sur la vie artificielle, pp.134-142, 1991.

B. Colson, Trust-regions algorithms for derivative-free optimization and nonlinear bilevel programming, 2003.

B. Colson and P. L. Toint, Optimizing partially separable functions without derivatives, Optimization Methods and Software, vol.7, issue.4-5, pp.493-508, 2005.
DOI : 10.1137/S1052623493250780

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.569.1838

A. R. Conn, Bilevel derivative-free optimization and its application to robust optimization, Optimization Methods and Software, vol.27, issue.3, 2010.
DOI : 10.1007/978-1-4615-6305-1

A. R. Conn, N. I. Gould, and P. L. Toint, Trust-Region Methods, MPS-SIAM Series on Optimization, SOIAM Philadelphia, 2000.
DOI : 10.1137/1.9780898719857

A. R. Conn, L. Digabel, and S. , Use of quadratic models with mesh-adaptive direct search for constrained black box optimization, Optimization Methods and Software, vol.17, issue.1
DOI : 10.1137/070691814

A. R. Conn, K. Scheinberg, and P. L. Toint, On the convergence of derivative-free methods for unconstrained optimization Approximation Theory and Optimization : Tributes to M, pp.83-108, 1997.

A. R. Conn, K. Scheinberg, and P. L. Toint, A derivative free optimization algorithm in practice, 7th AIAA/USAF/NASA/ISSMO Symposium on Multidisciplinary Analysis and Optimization, 1998.
DOI : 10.2514/6.1998-4718

A. R. Conn, K. Scheinberg, V. , and L. N. , Global Convergence of General Derivative-Free Trust-Region Algorithms to First- and Second-Order Critical Points, SIAM Journal on Optimization, vol.20, issue.1
DOI : 10.1137/060673424

A. R. Conn, K. Scheinberg, V. , and L. N. , Introduction to Derivative- Free Optimization, Society for Industrial and Applied MathematicsMPS-SIAM Series on Optimization), 2009.
DOI : 10.1137/1.9780898718768

A. R. Conn and P. L. Toint, An Algorithm using Quadratic Interpolation for Unconstrained Derivative Free Optimization, In Nonlinear Optimization and Applications, pp.27-47, 1996.
DOI : 10.1007/978-1-4899-0289-4_3

P. Contou-carrere, Algorithmes d'optimisation globale efficaces pour des fonctions fortement non linéaires, 2006.

R. Courant, Variational methods for the solution of problems of equilibrium and vibrations, Bulletin of the American Mathematical Society, vol.49, issue.1, pp.1-23, 1943.
DOI : 10.1090/S0002-9904-1943-07818-4

C. Darwin, On the Origin of Species by Means of Natural Selection, 1859.
DOI : 10.5962/bhl.title.24329

I. Das, D. , and J. , A closer look at drawbacks of minimizing wieighted sums of objectives for pareto set generation in multicriteria optimization problems, Structural Optimization, pp.63-69, 1997.

I. Das, D. , and J. , Normal-Boundary Intersection: A New Method for Generating the Pareto Surface in Nonlinear Multicriteria Optimization Problems, SIAM Journal on Optimization, vol.8, issue.3, pp.631-657, 1998.
DOI : 10.1137/S1052623496307510

K. Deb, S. Agrawal, A. Pratap, and T. Meyarivan, A fast and elitist multiobjective genetic algorithm: NSGA-II, IEEE Transactions on Evolutionary Computation, vol.6, issue.2, pp.182-197, 2002.
DOI : 10.1109/4235.996017

K. Deb, A. Pratap, and T. Meyarivan, Constrained test problems for multiobjective evolutionary optimization, First International Conference on Evolutionary Multi-Criterion Optimization, pp.284-298, 2001.

F. Delbos, Probì emes d'optimisation non linéaire avec contraintes en tomographie de réflexion 3D, 2004.

F. Delbos, J. Gilbert, and D. Sinoquet, Non linear optimization for reservoir characterization, ENGOPT International conference on engineering optimization, pp.1-5, 2008.

J. E. Dennis and I. Das, Normal-boundary intersection : A new method for generating the pareto surface in nonlinear multicriteria optimization problems, SIAM Journal on Optimization, vol.8, pp.631-657, 1998.

J. E. Dennis and R. B. Schnabel, Numerical Methods for Unconstrained Optimization and Nonlinear Equations, 1983.
DOI : 10.1137/1.9781611971200

J. E. Dennis and V. Torczon, Direct Search Methods on Parallel Machines, SIAM J. Optim, vol.1, pp.448-474, 1991.
DOI : 10.1007/978-3-642-48417-9_2

C. Dhaenens-flipo, Optimisation Combinatoire Multi-Objectif : Apport des Méthodes Coopératives et ContributionàContributionà L'Extraction de Connaissances, 2005.

D. Ding, Development of a data partition technique for gradient-based optimization methods in history matching, p.130473, 2010.

D. Ding, Improving perturbation designs for gradientbased optimization methods in history matching, ECMOR European Conference on the Mathematics of Oil Recovery, pp.6-9, 2010.

M. Diniz-ehrhardt, J. Martinez, and L. Pedroso, Derivative-free methods for nonlinear programming with general lower-level constraints, 2010.

L. J. Do-nascimento-guimarães, B. Horowitz, and S. M. Afonso, Global optimal solutions for reservoir engineering applications, EngOpt 2008 - International Conference on Engineering Optimization Rio de Janeiro, pp.1-05, 2008.

M. Dorigo, Optimization, Learning and Natural Algorithms, 1992.

J. Dréo, Adaptation de la méthode des colonies de fourmis pour l'optimisation en variables continues. Application en génie biomédical, 2004.

L. Dumas, Optimization and CFD, CFD-based Optimization for Automotive Aerodynamics, 2008.

L. Dumas, A. , and L. , Medical Applications of Genetic and Evolutionary Computation, 2010.

A. Emerick, E. Silva, B. Messer, L. Almeida, D. Szwarcman et al., Well Placement Optimization Using a Genetic Algorithm With Nonlinear Constraints, SPE Reservoir Simulation Symposium, 2009.
DOI : 10.2118/118808-MS

M. Emmerich, N. Beume, and B. Naujoks, An emo algorithm using the hypervolume measure as selection criterion, third international conference on evolutionary multy-criterion optimization, LNCS, vol.3410, pp.62-76, 2005.

S. S. Fan, Y. Liang, and E. Zhara, A genetic algorithm and a particle swarm optimizer hybridized with Nelder???Mead simplex search, Computers & Industrial Engineering, vol.50, issue.4, pp.50-401, 2006.
DOI : 10.1016/j.cie.2005.01.022

M. Feraille and D. Busby, Uncertainty management on a reservoir workflow, International Petroleum Technology Conference, 2009.
DOI : 10.2523/IPTC-13768-MS

M. Feraille, F. Roggero, E. Manceau, L. Y. Hu, I. Zabalza-mezghani et al., Application of Advanced History Matching Techniques to an Integrated Field Case Study, SPE Annual Technical Conference and Exhibition, 2003.
DOI : 10.2118/84463-MS

A. Fiacco and G. Mccormick, Nonlinear Programming : Sequential Unconstrained Minimization Techniques, 1968.
DOI : 10.1137/1.9781611971316

M. Fleischer, The measure of pareto optima. applications to multi-objective metaheuristics. EMO of LNCS, pp.519-533, 2003.

R. Fletcher, Practical Methods of Optimization, 1980.
DOI : 10.1002/9781118723203

R. Fletcher, Practical Methods of Optimization Constrained Optimization, 1981.

R. Fletcher, N. I. Gould, S. Leyffer, P. L. Toint, and A. Wächter, Global Convergence of a Trust-Region SQP-Filter Algorithm for General Nonlinear Programming, SIAM Journal on Optimization, vol.13, issue.3, 2002.
DOI : 10.1137/S1052623499357258

G. Font, D. Sinoquet, H. Langouët, M. Castagne, M. et al., Derivative free optimization method and physical simulations coupled with statistical models for transient engine calibration, 6th Conference Design of Experiments (DoE) in Engine Development, 2011.

A. Fornel, B. Noetinger, R. , and F. , Using Time Domain Seismic Attributes for History Matching, ECMOR X, 10th European Conference on the Mathematics of Oil Recovery, 2007.
DOI : 10.3997/2214-4609.201402493

L. Frimannslund and T. Steihaug, A generating set search method using curvature information, Computational Optimization and Applications, vol.29, issue.1, pp.105-121, 2007.
DOI : 10.1007/s10589-007-9038-8

K. Frisch, The logarithmic potential method for convex programming. Memorandum, 1955.

J. Gilbert, Optimisation Différentiable ? Théorie et Algorithmes, Syllabus de coursàcoursà l'ENSTA, 2003.

P. Gill, W. Murray, and M. Saunders, SNOPT : an SQP algorithm for large-scale constrained optimization, 1996.

P. Gill, W. Murray, M. Saunders, and M. Wright, User's guide for NP- SOL (version 4.0) : a Fortran package for nonlinear programming, 94305, 1986.

D. Ginsbourger, Métamodèles Multiples pour l'Approximation et l'Optimisation de Fonctions Numériques Multivariables, 2009.

D. E. Goldberg, Genetic algorithms in search, optimization and machine learning, 1989.

N. Gould, On the Convergence of a Sequential Penalty Function Method for Constrained Minimization, SIAM Journal on Numerical Analysis, vol.26, issue.1, pp.107-126, 1989.
DOI : 10.1137/0726007

N. Gould, D. Orban, and P. L. Toint, CUTEr and SifDec, ACM Transactions on Mathematical Software, vol.29, issue.4, pp.373-394, 2003.
DOI : 10.1145/962437.962439

S. Gratton, P. L. Toint, and A. Tröltzsch, An active-set trust-region method for derivative-free nonlinear bound-constrained optimization. Optimization Methods and Software, 2010.

D. Guérillot, R. , and F. , Matching the Future for the Evaluation of Extreme Reservoir Development Scenarios, IOR 1995, 8th European Symposium on Improved Oil Recovery, 1995.
DOI : 10.3997/2214-4609.201406934

H. Gutmann, A radial basis function method for global optimization, Journal of Global Optimization, vol.19, issue.3, pp.201-227, 2001.
DOI : 10.1023/A:1011255519438

H. Gutmann, Radial Basis Function Methods for Global Optimization, 2001.

R. T. Haftka, Combining global and local approximations, AIAA Journal, vol.29, issue.9, pp.1523-1525, 1991.
DOI : 10.2514/3.10768

S. Han, Superlinearly convergent variable metric algorithms for general nonlinear programming problems, Mathematical Programming, vol.14, issue.1, pp.263-282, 1976.
DOI : 10.1007/BF01580395

S. Han, A globally convergent method for nonlinear programming, Journal of Optimization Theory and Applications, vol.5, issue.3, pp.297-309, 1977.
DOI : 10.1007/BF00932858

N. Hansen, C. Igel, R. , and S. , Covariance matrix adaptation for multiobjective optimization, Evolutionary Computation, vol.15, issue.1, pp.1-28, 2007.

N. Hansen and N. Kern, Evaluating the CMA Evolution Strategy on Multimodal Test Functions, Eighth International Conference on Parallel Problem Solving from Nature PPSN VIII, Proceedings, pp.282-291, 2004.
DOI : 10.1007/978-3-540-30217-9_29

N. Hansen and A. Ostermeier, Adapting arbitrary normal mutation distributions in evolution strategies: the covariance matrix adaptation, Proceedings of IEEE International Conference on Evolutionary Computation, pp.312-317, 1996.
DOI : 10.1109/ICEC.1996.542381

N. Hansen and A. Ostermeier, Completely Derandomized Self-Adaptation in Evolution Strategies, Evolutionary Computation, vol.9, issue.2, pp.159-195, 2001.
DOI : 10.1016/0004-3702(95)00124-7

J. Holland, Adaptation in natural and artificial systems, 1975.

R. Hooke, J. , and T. A. , `` Direct Search'' Solution of Numerical and Statistical Problems, Journal of the ACM, vol.8, issue.2, pp.212-229, 1961.
DOI : 10.1145/321062.321069

D. Huang, A. Tt, N. Wi, N. , and Z. , 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

T. Ishikawa, M. , and M. , An optimization method based on radial basis function, IEEE Transactions on Magnetics, vol.33, issue.2, pp.1868-1871, 1997.
DOI : 10.1109/20.582647

T. Ishikawa, Y. , T. , M. , and M. , A combined method for the global optimization using radial basis function and deterministic approach, IEEE Transactions on Magnetics, vol.35, issue.3, pp.1730-1733, 1999.
DOI : 10.1109/20.767363

S. Jakobsson, M. Patriksson, J. Rudholm, and A. Wojciechowski, A method for simulation based optimization using radial basis functions, Optimization and Engineering, vol.90, issue.4, 2009.
DOI : 10.1007/s11081-009-9087-1

S. Jakobsson, M. Saif-ul-hasnain, R. Rundqvist, F. Edelvik, B. Andersson et al., Combustion engine optimization: a multiobjective approach, Optimization and Engineering, vol.85, issue.2, 2009.
DOI : 10.1007/s11081-009-9090-6

M. Jebalia, Optimisation par Stratégies d' ´ Evolution : Convergence et vitesses de convergence pour des fonctions bruitées -Résolution d'unprobì eme d'identification, 2008.

F. Jiménez and J. L. Verdegay, Constrained multiobjective optimization by evolutionary algorithms, Proceedings of the International ICSC Symposium on Engineering of Intelligent Systems (EIS'98), pp.266-271, 1998.

D. Jones, Large-scale multi-disciplinary mass optimization in the auto industry. Presented at the MOPTA, Conference, 2008.

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

D. R. Jones, M. Schonlau, W. , and W. J. , 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

N. Jozefowiez, Modélisation et Résolution Approchée deProbì emes de Tournées Multi-Objectif, 2004.

J. Käck, Constrained global optimization with radial basis functions. Tech. rep, 2004.

C. Kelley, Iterative methods for optimization, SIAM, 1999.
DOI : 10.1137/1.9781611970920

J. Kennedy and R. Eberhart, Particle swarm optimization, Proceedings of ICNN'95, International Conference on Neural Networks, pp.1942-1948, 1995.
DOI : 10.1109/ICNN.1995.488968

S. Kirkpatrick, C. D. Gelatt, and M. P. Vecchi, Optimization by Simulated Annealing, Science, vol.220, issue.4598, pp.671-680, 1983.
DOI : 10.1126/science.220.4598.671

J. Knowles, ParEGO: a hybrid algorithm with on-line landscape approximation for expensive multiobjective optimization problems, IEEE Transactions on Evolutionary Computation, vol.10, issue.1, pp.50-66, 2006.
DOI : 10.1109/TEVC.2005.851274

P. Koduru, S. Das, W. , and S. M. , A particle swarm optimization-nelder mead hybrid algorithm for balanced exploration and exploitation in multidimensional search space, Proceedings, International Conference on Artificial Intelligence, pp.457-464, 2006.

T. G. Kolda, R. M. Lewis, and V. Torczon, Optimization by Direct Search: New Perspectives on Some Classical and Modern Methods, SIAM Review, vol.45, issue.3, pp.385-482, 2003.
DOI : 10.1137/S003614450242889

H. Langouët, Optimisation multi-objectifs pour la calibration des moteurs, 2007.

H. Langouët, F. Delbos, D. Sinoquet, D. Veiga, and S. , A Derivative Free Optimization Method for Reservoir Characterization Inverse Problem, 12th European Conference on the Mathematics of Oil Recovery, pp.6-9, 2010.
DOI : 10.3997/2214-4609.20144992

H. Langouët, L. Métivier, D. Sinoquet, T. , and Q. , Optimization for engine calibration, ENGOPT International conference on engineering optimization, pp.1-5, 2008.

H. Langouët, L. Métivier, D. Sinoquet, T. , and Q. , Engine calibration: multi-objective constrained optimization of engine maps, Optimization and Engineering, vol.21, issue.2, 2010.
DOI : 10.1007/s11081-011-9140-8

H. Langouët and D. Sinoquet, Derivative free optimization under constraints, ENBIS EMSE, pp.1-3, 2009.

J. B. Lasserre, Global Optimization with Polynomials and the Problem of Moments, SIAM Journal on Optimization, vol.11, issue.3, pp.796-817, 2000.
DOI : 10.1137/S1052623400366802

J. B. Lasserre, Moments, Positive Polynomials and Their Applications, 2009.
DOI : 10.1142/p665

M. Marazzi and J. Nocedal, Wedge trust region methods for derivative free optimization, Mathematical Programming, vol.91, issue.2, pp.289-305, 2002.
DOI : 10.1007/s101070100264

M. Mckay, R. Beckman, and W. Conover, A comparison of three methods for selecting values of input variables in the analysis of outpit from a computer code, Technometrics, vol.21, pp.239-246, 1979.

N. Metla, F. Delbos, S. Da-veiga, and D. Sinoquet, Constrained Nonlinear Optimization for Extreme Scenarii Evaluation in Reservoir Characterization, 12th European Conference on the Mathematics of Oil Recovery, pp.6-9, 2010.
DOI : 10.3997/2214-4609.20145035

Z. Michalewicz, D. Dasgupta, R. Riche, and M. Schoenauer, Evolutionary algorithms for constrained engineering problems, Computers & Industrial Engineering, vol.30, issue.4, pp.851-870, 1996.
DOI : 10.1016/0360-8352(96)00037-X

Z. Michalewicz and G. Nazhiyath, Genocop III: a co-evolutionary algorithm for numerical optimization problems with nonlinear constraints, Proceedings of 1995 IEEE International Conference on Evolutionary Computation, pp.647-651, 1995.
DOI : 10.1109/ICEC.1995.487460

J. J. Moré and S. M. Wild, Benchmarking Derivative-Free Optimization Algorithms, SIAM Journal on Optimization, vol.20, issue.1, pp.172-191, 2009.
DOI : 10.1137/080724083

L. Métivier, Modélisation et optimisation des cartographies d'un moteur, 2006.

R. H. Myers, M. , and D. C. , Response Surface Methodology : Process and Product Optimization Using Designed Experiments. Wiley series in probability and statistics, 1995.

J. A. Nelder, M. , and R. , A Simplex Method for Function Minimization, The Computer Journal, vol.7, issue.4, pp.308-313, 1965.
DOI : 10.1093/comjnl/7.4.308

J. Nocedal, W. , and S. , Numerical Optimization, 1999.
DOI : 10.1007/b98874

R. Oeuvray, Trust-Region Methods Based On Radial Basis Functions With Application To Biomedical Imaging, 2005.

U. G. Palomares and O. Mangasarian, Superlinearly convergent quasi-newton algorithms for nonlinearly constrained optimization problems, Mathematical Programming, vol.8, issue.1, pp.1-13, 1976.
DOI : 10.1007/BF01580366

V. Pareto, Cours d'´ economie politique, Rouge, vol.1, issue.2, 1896.

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.
DOI : 10.1093/comjnl/7.2.155

M. J. Powell, Algorithms for nonlinear constraints that use lagrangian functions, Mathematical Programming, vol.5, issue.1, pp.224-248, 1978.
DOI : 10.1007/BF01588967

M. J. Powell, THE CONVERGENCE OF VARIABLE METRIC METHODS FOR NONLINEARLY CONSTRAINED OPTIMIZATION CALCULATIONS, In Nonlinear Programming, vol.3, pp.27-63, 1978.
DOI : 10.1016/B978-0-12-468660-1.50007-4

M. J. Powell, A fast algorithm for nonlinearly constrained optimization calculations In Numerical Analysis Dundee, 630 in Lecture Notes in Mathematics, pp.144-157, 1977.

M. J. Powell, Advances In Optimization And Numerical Analysis A direct search optimization method that models the objective and constraint functions by linear interpolation, pp.51-67, 1994.

M. J. Powell, A direct search optimization method that models the objective by quadratic interpolation, Presentation at the 5th Stockholm Optimization Days, 1994.

M. J. Powell, Direct search algorithms for optimization calculations, Acta Numerica, vol.8, pp.287-336, 1998.
DOI : 10.1007/BF00933295

M. J. Powell, A quadratic model trust region method for unconstrained minimization without derivatives, Presentation at the International Conference on Nonlinear Programming and Variational Inequalities, 1998.

M. J. Powell, UOBYQA: unconstrained optimization by quadratic approximation, Mathematical Programming, vol.92, issue.3, pp.555-582, 2002.
DOI : 10.1007/s101070100290

M. J. Powell, Least Frobenius norm updating of quadratic models that satisfy interpolation conditions, Mathematical Programming, vol.100, issue.1, pp.183-215, 2004.
DOI : 10.1007/s10107-003-0490-7

M. J. Powell, The NEWUOA software for unconstrained optimization without derivatives, Tech. rep., Department of Applied Mathematics and Theoretical Physics Centre for Mathematical Sciences, 2006.
DOI : 10.1007/0-387-30065-1_16

M. J. Powell, Developments of newuoa for unconstrained minimization without derivatives, 2007.

M. J. Powell, A view of algorithms for optimization without derivatives, 2007.

M. J. Powell, The bobyqa algorithm for bound constrained optimization without derivatives, Department of Applied Mathematics and Theoretical Physics, Centre for Mathematical Sciences, 2009.

M. J. Powell, On the convergence of trust region algorithms for unconstrained minimization without derivatives, Department of Applied Mathematics and Theoretical Physics, Centre for Mathematical Sciences, 2011.
DOI : 10.1007/s10589-012-9483-x

I. Rechenberg, Evolutionsstrategie : Optimierung technisher systeme nache prinzipien der biologischen evolution. Werkstatt Bionik und Evolutionstechnik, 1973.

R. G. Regis, Radial basis function algorithms for large-scale nonlinearly constrained black-box optimization, 20th International Symposium on Mathematical Programming Chicago, pp.113-135, 2009.

R. G. Regis and C. A. Shoemaker, Constrained Global Optimization of Expensive Black Box Functions Using Radial Basis Functions, Journal of Global Optimization, vol.7, issue.1, pp.153-171, 2005.
DOI : 10.1007/s10898-004-0570-0

R. G. Regis and C. A. Shoemaker, Improved Strategies for Radial basis Function Methods for Global Optimization, Journal of Global Optimization, vol.90, issue.1, pp.113-135, 2007.
DOI : 10.1007/s10898-006-9040-1

R. G. Regis and C. A. Shoemaker, Parallel radial basis function methods for the global optimization of expensive functions, European Journal of Operational Research, vol.182, issue.2, pp.514-535, 2007.
DOI : 10.1016/j.ejor.2006.08.040

R. G. Regis and C. A. Shoemaker, A Stochastic Radial Basis Function Method for the Global Optimization of Expensive Functions, INFORMS Journal on Computing, vol.19, issue.4, pp.497-509, 2007.
DOI : 10.1287/ijoc.1060.0182

H. H. Rosenbrock, An Automatic Method for Finding the Greatest or Least Value of a Function, The Computer Journal, vol.3, issue.3, pp.175-184, 1960.
DOI : 10.1093/comjnl/3.3.175

O. Roudenko, Application des Algorithmes Evolutionnaires auxprobì emes d'optimisation multi-critère avec contraintes, 2004.

J. Rudholm and A. Wojciechowsjki, A method for simulation based optimization using radial basis functions. Master's thesis, university of Göteborg, 2007.

K. Schittkowski, NLPQL: A fortran subroutine solving constrained nonlinear programming problems, Annals of Operations Research, vol.14, issue.1-4, pp.485-500, 1985.
DOI : 10.1007/BF02739235

A. Schmied, Méthodes stochastiques d'optimisation appliquéesappliquéesà la mise au point des moteurs, 2003.

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

M. Schonlau, W. , and W. , Global optimization with nonparametric function fitting, Proceedings of the Section on Physical and Engineering Sciences, pp.183-186, 1996.

H. Schwefel, Evolution and optimum seeking. Sixth-Generation Computer Technology Series, 1995.

D. B. Serafini, A Framework for Managing Models in Nonlinear Optimization of Computationally Expensive Functions, 1998.

D. Sinoquet, D. , and F. , Adapted Nonlinear Optimization Method for Production Data and 4D Seismic Inversion, 11th European Conference on the Mathematics of Oil Recovery, pp.8-11, 2008.
DOI : 10.3997/2214-4609.20146436

J. Søndergaard, Optimization Using Surrogate Models ? by the space mapping technique, 2003.

W. Spendley, G. Hext, and F. Himsworth, Sequential Application of Simplex Designs in Optimisation and Evolutionary Operation, Technometrics, vol.39, issue.4, pp.441-461, 1962.
DOI : 10.1214/aoms/1177707047

V. Torczon, On the Convergence of the Multidirectional Search Algorithm, SIAM Journal on Optimization, vol.1, issue.1, pp.123-145, 1991.
DOI : 10.1137/0801010

V. Torczon, On the Convergence of Pattern Search Algorithms, SIAM Journal on Optimization, vol.7, issue.1, pp.1-25, 1997.
DOI : 10.1137/S1052623493250780

V. Toropov, Simulation approach to structural optimization, Structural Optimization, vol.11, issue.1, pp.37-46, 1989.
DOI : 10.1007/BF01743808

S. Touzani, Response surface methods based on analysis of variance expansion for sensitivity analysis, 2011.
URL : https://hal.archives-ouvertes.fr/tel-00614038

O. Ugur, B. Karasozen, M. Schäfer, Y. , and K. , Derivative free optimization methods for optimizing stirrer configurations. Derivative free optimization methods for optimizing stirrer configurations, European Journal of Operational Research, issue.3, pp.855-863, 2008.

F. Vanden-berghen, CONDOR : a constrained, non-linear, derivative-free parallel optimizer for continuous, high computing load, noisy objective functions, Faculté des Sciences Appliquées, 2004.

F. Vanden-berghen, Constrained, non-linear, direct, parallel optimization algorithm using a trust region method for high-computing load, continuous, noisy functions, Condor. Tech. rep, 2007.

F. Vanden-berghen and H. Bersini, CONDOR, a new parallel, constrained extension of Powell's UOBYQA algorithm: Experimental results and comparison with the DFO algorithm, Journal of Computational and Applied Mathematics, vol.181, issue.1, pp.157-175, 2005.
DOI : 10.1016/j.cam.2004.11.029

M. Vangrieken, Optimisation pour l'apprentisage et apprentisage pour l'optimisation, 2004.

A. Vaz and L. N. Vicente, A particle swarm pattern search method for bound constrained global optimization, Journal of Global Optimization, vol.31, issue.1, pp.197-219, 2007.
DOI : 10.1007/s10898-007-9133-5

J. Villemonteix, Optimisation De Fonctions Coûteuses : Modèles Gaussiens Pour Une Utilisation Efficace Du Budget D'´ evaluations : Théorie Et Pratique Industrielle, 2008.

J. Villemonteix, E. Vazquez, M. Sidorkiewicz, and E. Walter, Informational approach to the global optimization (iago) of expensive to evaluate functions, GdR MASCOT-NUM CEA Cadarache, 2008.

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

T. Weise, Global Optimization Algorithms -Theory and Application, 2008.

S. M. Wild, Mnh : A derivative-free optimization algorithm using minimal norm hessians, Tech. rep., School of Operations Research & Information Engineering, 2008.

S. M. Wild, Derivative-Free Optimization Algorithms For Computationally Expensive Functions, 2009.

S. M. Wild, R. G. Regis, and C. A. Shoemaker, ORBIT: Optimization by Radial Basis Function Interpolation in Trust-Regions, SIAM Journal on Scientific Computing, vol.30, issue.6, pp.3197-3219, 2008.
DOI : 10.1137/070691814

S. M. Wild and C. Shoemaker, Global Convergence of Radial Basis Function Trust Region Derivative-Free Algorithms, SIAM Journal on Optimization, vol.21, issue.3, 2011.
DOI : 10.1137/09074927X

R. Wilson, A simplicial algorithm for concave programming, 1963.

D. Winfield, Function and functional optimization by interpolation in data tables, 1969.

D. Winfield, Function Minimization by Interpolation in a Data Table, IMA Journal of Applied Mathematics, vol.12, issue.3, pp.339-347, 1973.
DOI : 10.1093/imamat/12.3.339

T. A. Winslow, R. J. Trew, P. Gilmore, K. , and C. T. , Doping profiles for optimum class B performance of GaAs MESFET amplifiers, [1991] Proceedings IEEE/Cornell Conference on Advanced Concepts in High Speed Semiconductor Devices and Circuits, pp.188-197, 1991.
DOI : 10.1109/CORNEL.1991.170048

E. Zahara and Y. Kao, Hybrid Nelder???Mead simplex search and particle swarm optimization for constrained engineering design problems, Expert Systems with Applications, vol.36, issue.2, pp.3880-3886, 2009.
DOI : 10.1016/j.eswa.2008.02.039

H. Zhang, A. R. Conn, and K. Scheinberg, A Derivative-Free Algorithm for Least-Squares Minimization, SIAM Journal on Optimization, vol.20, issue.6, 2009.
DOI : 10.1137/09075531X

E. Zitzler and L. Thiele, Multiobjective optimization using evolutionary algorithms ??? A comparative case study, Fifth International Conference on Parallel Problem Solving from Nature, pp.292-301, 1998.
DOI : 10.1007/BFb0056872