M. A. Abramson, C. Audet, G. Couture, J. E. Dennis-jr, S. L. Digabel et al., The NOMAD project

M. A. Abramson, O. A. Brezhneva, J. E. Dennis-jr, and R. L. , Pattern search in the presence of degenerate linear constraints, Optimization Methods and Software, vol.2, issue.3, pp.297-319, 2008.
DOI : 10.1137/S1052623493250780

G. Aditya, B. Akhilesh, and C. Kuntal, A comprehensive review of image smoothing techniques, Inter. J. of Advanced Research in Computer Engineering & Technology, 2012.

N. Ahmed, T. Natarajan, and K. R. Rao, Discrete cosine transfom, IEEE Trans. Comput, vol.23, issue.1, pp.90-93, 1974.
DOI : 10.1109/t-c.1974.223784

M. M. Ali, C. Khompatraporn, and Z. B. Zabinsky, A Numerical Evaluation of Several Stochastic Algorithms on Selected Continuous Global Optimization Test Problems, Journal of Global Optimization, vol.3, issue.3, pp.635-672, 2005.
DOI : 10.1007/s10898-004-9972-2

L. Altenberg, Advances in genetic programming. chapter The Evolution of Evolvability in Genetic Programming, pp.47-74, 1994.

P. R. Amestoy, I. S. Duff, J. Koster, and J. Excellent, A Fully Asynchronous Multifrontal Solver Using Distributed Dynamic Scheduling, SIAM Journal on Matrix Analysis and Applications, vol.23, issue.1, pp.15-41, 2001.
DOI : 10.1137/S0895479899358194

URL : https://hal.archives-ouvertes.fr/hal-00808293

P. R. Amestoy, A. Guermouche, J. Excellent, and S. Pralet, Hybrid scheduling for the parallel solution of linear systems, Parallel Computing, vol.32, issue.2, pp.136-156, 2006.
DOI : 10.1016/j.parco.2005.07.004

URL : https://hal.archives-ouvertes.fr/hal-00358623

D. V. Arnold, Optimal Weighted Recombination, Foundations of Genetic Algorithms, pp.215-237, 2005.
DOI : 10.1007/11513575_12

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

L. Arnold, A. Auger, N. Hansen, and Y. Ollivier, Information-geometric optimization algorithms: A unifying picture via invariance principles, 2013.
URL : https://hal.archives-ouvertes.fr/hal-00601503

C. Atkeson, A. W. Moore, and S. Schaal, Locally Weighted Learning, Artif. Intell. Rev, vol.11, issue.1-5, pp.11-73, 1997.
DOI : 10.1007/978-94-017-2053-3_2

C. Audet, A short proof on the cardinality of maximal positive bases, Optimization Letters, vol.2, issue.1, pp.191-194, 2011.
DOI : 10.1007/s11590-010-0229-3

C. Audet, S. L. Digabel, and C. Tribes, NOMAD user guide, 2009.

C. Audet and J. E. Dennis-jr, Analysis of Generalized Pattern Searches, SIAM Journal on Optimization, vol.13, issue.3, pp.889-903, 2002.
DOI : 10.1137/S1052623400378742

C. Audet and J. E. Dennis-jr, Mesh Adaptive Direct Search Algorithms for Constrained Optimization, SIAM Journal on Optimization, vol.17, issue.1, pp.188-217, 2006.
DOI : 10.1137/040603371

C. Audet and J. E. Dennis-jr, A Progressive Barrier for Derivative-Free Nonlinear Programming, SIAM Journal on Optimization, vol.20, issue.1, pp.445-472, 2009.
DOI : 10.1137/070692662

A. Auger, Convergence results for the <mml:math altimg="si1.gif" overflow="scroll" xmlns:xocs="http://www.elsevier.com/xml/xocs/dtd" xmlns:xs="http://www.w3.org/2001/XMLSchema" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns="http://www.elsevier.com/xml/ja/dtd" xmlns:ja="http://www.elsevier.com/xml/ja/dtd" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:tb="http://www.elsevier.com/xml/common/table/dtd" xmlns:sb="http://www.elsevier.com/xml/common/struct-bib/dtd" xmlns:ce="http://www.elsevier.com/xml/common/dtd" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:cals="http://www.elsevier.com/xml/common/cals/dtd"><mml:mo stretchy="false">(</mml:mo><mml:mn>1</mml:mn><mml:mo>,</mml:mo><mml:mi>??</mml:mi><mml:mo stretchy="false">)</mml:mo></mml:math>-SA-ES using the theory of <mml:math altimg="si2.gif" overflow="scroll" xmlns:xocs="http://www.elsevier.com/xml/xocs/dtd" xmlns:xs="http://www.w3.org/2001/XMLSchema" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns="http://www.elsevier.com/xml/ja/dtd" xmlns:ja="http://www.elsevier.com/xml/ja/dtd" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:tb="http://www.elsevier.com/xml/common/table/dtd" xmlns:sb="http://www.elsevier.com/xml/common/struct-bib/dtd" xmlns:ce="http://www.elsevier.com/xml/common/dtd" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:cals="http://www.elsevier.com/xml/common/cals/dtd"><mml:mi>??</mml:mi></mml:math>-irreducible Markov chains, Theoretical Computer Science, vol.334, issue.1-3, pp.35-69, 2005.
DOI : 10.1016/j.tcs.2004.11.017

A. Auger, D. Brockhoff, and N. Hansen, Benchmarking the local metamodel CMA-ES on the noiseless BBOB'2013 test bed, Proceeding of the fifteenth annual conference companion on Genetic and evolutionary computation conference companion, GECCO '13 Companion, pp.1225-1232, 2013.
DOI : 10.1145/2464576.2482701

URL : https://hal.archives-ouvertes.fr/hal-00825840

A. Auger and N. Hansen, A Restart CMA Evolution Strategy With Increasing Population Size, 2005 IEEE Congress on Evolutionary Computation, pp.1769-1776, 2005.
DOI : 10.1109/CEC.2005.1554902

A. Auger, N. Hansen, Z. J. Perez, R. Ros, and M. Schoenauer, Experimental Comparisons of Derivative Free Optimization Algorithms, 8th International Symposium on Experimental Algorithms, number 5526, pp.3-15, 2009.
DOI : 10.1007/978-3-642-02011-7_3

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

T. Bäck, Evolutionary algorithms in theory and practice: Evolution strategies, evolutionary programming, genetic algorithms, 1996.

T. Bäck and M. Schütz, Evolution strategies for mixed?integer optimization of optical multilayer systems, In EVOLUTIONARY PROGRAMMING IV ? PROC. FOURTH ANNUAL CONF. EVOLUTIONARY PROGRAMMING, pp.33-51, 1995.

T. Bäck and H. Schwefel, An Overview of Evolutionary Algorithms for Parameter Optimization, Evolutionary Computation, vol.1, issue.1, pp.1-23, 1993.
DOI : 10.1162/evco.1993.1.1.1

A. S. Bandeira, K. Scheinbeerg, and L. N. Vicente, Convergence of Trust-Region Methods Based on Probabilistic Models, SIAM Journal on Optimization, vol.24, issue.3, 2013.
DOI : 10.1137/130915984

A. S. Bandeira, K. Scheinberg, and L. N. Vicente, Computation of sparse low degree interpolating polynomials and their application to derivative-free optimization, Mathematical Programming, vol.10, issue.1, pp.223-257, 2012.
DOI : 10.1007/s10107-012-0578-z

J. Bérenger, A perfectly matched layer for the absorption of electromagnetic waves, Journal of Computational Physics, vol.114, issue.2, pp.185-200, 1994.
DOI : 10.1006/jcph.1994.1159

H. Beyer, The Theory of Evolution Strategies, 1998.
DOI : 10.1007/978-3-662-04378-3

H. Beyer, Evolutionary algorithms in noisy environments: theoretical issues and guidelines for practice, Computer Methods in Applied Mechanics and Engineering, vol.186, issue.2-4, pp.239-267, 2000.
DOI : 10.1016/S0045-7825(99)00386-2

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

A. Bienvenüe and O. François, Global convergence for evolution strategies in spherical problems: some simple proofs and difficulties, Theoretical Computer Science, vol.306, issue.1-3, pp.269-289, 2003.
DOI : 10.1016/S0304-3975(03)00284-6

F. Billette, S. L. Bégat, P. Podvin, and G. Lambaré, Practical aspects and applications of 2D stereotomography, GEOPHYSICS, vol.68, issue.3, pp.1008-1021, 2003.
DOI : 10.1190/1.1581072

F. Billette and G. Lambaré, Velocity macro-model estimation from seismic reflection data by stereotomography, Geophysical Journal International, vol.135, issue.2, pp.671-690, 1998.
DOI : 10.1046/j.1365-246X.1998.00632.x

A. J. Booker, J. E. Dennis-jr, P. D. Frank, D. B. Serafini, V. Torczon et al., A rigorous framework for optimization of expensive functions by surrogates. Structural and Multidisciplinary Optimization, pp.1-13, 1998.

Z. Bouzarkouna, Well placement optimization, 2012.
URL : https://hal.archives-ouvertes.fr/tel-00690456

R. Brossier, Imagerie sismiquè a deux dimensions des milieux visco-´ elastiques par inversion des formes d'ondes : développements méthodologiques et applications, 2009.

L. Bull, Learning Classifier Systems, Soft Computing - A Fusion of Foundations, Methodologies and Applications, vol.6, issue.3-4, p.14, 2004.
DOI : 10.1007/s005000100110

H. Calandra, S. Gratton, R. Lago, X. Pinel, and X. Vasseur, Two-Level preconditioned Krylov subspace methods for the solution of three-dimensional heterogeneous Helmholtz problems in seismics, Numerical Analysis and Applications, vol.5, issue.2, pp.175-191, 2012.
DOI : 10.1134/S1995423912020127

L. M. Carvalho, S. Gratton, R. Lago, and X. Vasseur, A Flexible Generalized Conjugate Residual Method with Inner Orthogonalization and Deflated Restarting, SIAM Journal on Matrix Analysis and Applications, vol.32, issue.4, pp.1212-1235, 2011.
DOI : 10.1137/100786253

URL : https://hal.archives-ouvertes.fr/hal-00650239

R. Chiong, T. Weise, and Z. Michalewicz, Variants of evolutionary algorithms for real-world applications, 2011.
DOI : 10.1007/978-3-642-23424-8

F. H. Clarke, Optimization and nonsmooth analysis, 1983.
DOI : 10.1137/1.9781611971309

C. A. Coello, Theoretical and numerical constraint-handling techniques used with evolutionary algorithms: a survey of the state of the art, Computer Methods in Applied Mechanics and Engineering, vol.191, issue.11-12, pp.1245-1287, 2002.
DOI : 10.1016/S0045-7825(01)00323-1

C. A. Coello and E. M. Montes, Constraint-handling in genetic algorithms through the use of dominance-based tournament selection, Advanced Engineering Informatics, vol.16, issue.3, pp.193-203, 2002.
DOI : 10.1016/S1474-0346(02)00011-3

G. Cohen, Higher-order numerical methods for transient wave equations, 2002.
URL : https://hal.archives-ouvertes.fr/hal-01166961

M. D. Collins and W. A. Kuperman, Nonlinear inversion for ocean???bottom properties, The Journal of the Acoustical Society of America, vol.92, issue.5, pp.2770-2782, 1992.
DOI : 10.1121/1.404394

A. R. Conn and S. L. , Use of quadratic models with mesh-adaptive direct search for constrained black box optimization, Optimization Methods and Software, vol.17, issue.1, pp.139-158, 2013.
DOI : 10.1137/070691814

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

A. R. Conn, K. Scheinberg, and L. N. Vicente, Geometry of sample sets in derivative-free optimization: polynomial regression and underdetermined interpolation, IMA Journal of Numerical Analysis, vol.28, issue.4, pp.721-748, 2008.
DOI : 10.1093/imanum/drn046

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, pp.387-415, 2009.
DOI : 10.1137/060673424

A. R. Conn, K. Scheinberg, and L. N. Vicente, Introduction to derivative-free optimization, MPS-SIAM Series on Optimization. SIAM, 2009.
DOI : 10.1137/1.9780898718768

A. L. Custódio, H. Rocha, and L. N. Vicente, Incorporating minimum Frobenius norm models in??direct search, Computational Optimization and Applications, vol.28, issue.2, pp.265-278, 2010.
DOI : 10.1007/s10589-009-9283-0

A. L. Custódio and L. N. Vicente, Using Sampling and Simplex Derivatives in Pattern Search Methods, SIAM Journal on Optimization, vol.18, issue.2, pp.537-555, 2007.
DOI : 10.1137/050646706

I. Daubechies, Ten lectures on wavelets, MPS-SIAM. SIAM, 1992.

C. Davis, Theory of Positive Linear Dependence, American Journal of Mathematics, vol.76, issue.4, pp.733-746, 1954.
DOI : 10.2307/2372648

Y. Diouane, H. Calandra, S. Gratton, and X. Vasseur, A Parallel Evolution Strategy for Acoustic Full-Waveform Inversion, EAGE Workshop on High Performance Computing for Upstream, 2014.
DOI : 10.3997/2214-4609.20141923

Y. Diouane, S. Gratton, and L. N. Vicente, Globally convergente evolution strategies, Math. Program
DOI : 10.1007/s10107-014-0793-x

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

Y. Diouane, S. Gratton, and L. N. Vicente, Globally convergent evolution strategies for constrained optimization, Computational Optimization and Applications, vol.14, issue.2
DOI : 10.1007/s10589-015-9747-3

URL : https://hal.archives-ouvertes.fr/hal-01391788

E. D. Dolan and J. J. Moré, Benchmarking optimization software with performance profiles, Mathematical Programming, vol.91, issue.2, pp.201-213, 2002.
DOI : 10.1007/s101070100263

URL : http://arxiv.org/abs/cs/0102001

E. D. Dolan, J. J. Moré, and T. S. Munson, Optimality Measures for Performance Profiles, SIAM Journal on Optimization, vol.16, issue.3, pp.891-909, 2006.
DOI : 10.1137/040608015

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

G. Fasano, J. L. Morales, and J. Nocedal, On the geometry phase in model-based algorithms for derivative-free optimization, Optimization Methods and Software, vol.24, issue.1, pp.145-154, 2009.
DOI : 10.1080/10556780802409296

R. Fletcher and S. Leyffer, Nonlinear programming without a penalty function, Mathematical Programming, vol.91, issue.2, pp.239-269, 2002.
DOI : 10.1007/s101070100244

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

C. M. Fonseca and P. J. Fleming, An Overview of Evolutionary Algorithms in Multiobjective Optimization, Evolutionary Computation, vol.3, issue.1, pp.1-16, 1995.
DOI : 10.1162/evco.1994.2.3.221

S. Forrest and A. S. Perelson, Genetic algorithms and the immune system
DOI : 10.1007/BFb0029771

O. Gauthier, J. Virieux, and A. Tarantola, Two???dimensional nonlinear inversion of seismic waveforms: Numerical results, GEOPHYSICS, vol.51, issue.7, pp.1387-1403, 1986.
DOI : 10.1190/1.1442188

S. Gelly, S. Ruette, and O. Teytaud, Comparison-Based Algorithms Are Robust and Randomized Algorithms Are Anytime, Evolutionary Computation, vol.26, issue.3, pp.411-434, 2007.
DOI : 10.1137/0801010

URL : https://hal.archives-ouvertes.fr/inria-00173221

P. Gerstoft, probability distributions, The Journal of the Acoustical Society of America, vol.95, issue.2, pp.770-782, 1994.
DOI : 10.1121/1.408387

N. I. 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, vol.111, issue.4-5, pp.873-894, 2011.
DOI : 10.1093/imanum/drm047

S. Gratton, C. W. Royer, L. N. Vicente, and Z. Zhang, Direct Search Based on Probabilistic Descent, SIAM Journal on Optimization, vol.25, issue.3, 2014.
DOI : 10.1137/140961602

S. Gratton and L. N. Vicente, A Merit Function Approach for Direct Search, SIAM Journal on Optimization, vol.24, issue.4, 2014.
DOI : 10.1137/130917661

G. W. Greenwood and Q. J. Zhu, Convergence in evolutionary programs with selfadaptation, Evolutionary Computation, vol.9, pp.57-147, 2001.

B. Greer, Numerical optimization with neuroevolution, Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600), 2002.
DOI : 10.1109/CEC.2002.1006267

J. D. Griffin, T. G. Kolda, and R. M. Lewis, Asynchronous Parallel Generating Set Search for Linearly Constrained Optimization, SIAM Journal on Scientific Computing, vol.30, issue.4, pp.1892-1924, 2008.
DOI : 10.1137/060664161

N. Hansen, The CMA Evolution Strategy: A tutorial, 2011.
URL : https://hal.archives-ouvertes.fr/hal-01297037

N. Hansen, A. Auger, R. R. Raymond, S. Finck, and P. Po?ík, Comparing results of 31 algorithms from the black-box optimization benchmarking BBOB-2009, Proceedings of the 12th annual conference comp on Genetic and evolutionary computation, GECCO '10, pp.1689-1696, 2010.
DOI : 10.1145/1830761.1830790

URL : https://hal.archives-ouvertes.fr/hal-00545727

N. Hansen, S. Fincky, R. Rosz, and A. Auger, Real-parameter black-box optimization benchmarking 2010: Noisy functions definitions, 2010.

N. Hansen, S. Fincky, R. Rosz, and A. Auger, Real-parameter black-box optimization benchmarking 2010: Noiseless functions definitions, 2010.

N. Hansen, S. D. Müller, and P. Koumoutsakos, Reducing the Time Complexity of the Derandomized Evolution Strategy with Covariance Matrix Adaptation (CMA-ES), Evolutionary Computation, vol.11, issue.1, pp.1-18, 2003.
DOI : 10.1162/106365601750190398

N. Hansen, A. S. Niederberger, L. Guzzella, and P. Koumoutsakos, A Method for Handling Uncertainty in Evolutionary Optimization With an Application to Feedback Control of Combustion, IEEE Transactions on Evolutionary Computation, vol.13, issue.1, pp.180-197, 2009.
DOI : 10.1109/TEVC.2008.924423

URL : https://hal.archives-ouvertes.fr/inria-00276216

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

N. Hansen, A. Ostermeier, and A. Gawelczyk, On the adaptation of arbitrary normal mutation distributions in evolution strategies: The generating set adaptation, Proceedings of the Sixth International Conference on Genetic Algorithms, pp.57-64, 1995.

A. Hedar and M. Fukushima, Derivative-Free Filter Simulated Annealing Method for Constrained Continuous Global Optimization, Journal of Global Optimization, vol.6, issue.1, 2004.
DOI : 10.1007/s10898-005-3693-z

A. Henderson, ParaView Guide. A Parallel Visualization Application, 2007.

F. Herrera, M. Lozano, and J. L. Verdegay, Tackling real-coded genetic algorithms: Operators and tools for behavioural analysis, Artificial Intelligence Review, vol.12, issue.4, pp.265-319, 1998.
DOI : 10.1023/A:1006504901164

W. Hock and K. Schittkowski, Test Examples for Nonlinear Programming Codes, 1981.
DOI : 10.1007/978-3-642-48320-2

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

J. H. Holland, Adaptation in natural and artificial systems: An introductory analysis with applications to biology, control and artificial intelligence, 1992.

W. Huyer and A. Neumaier, Global optimization by multilevel coordinate search, Journal of Global Optimization, vol.14, issue.4, pp.331-355, 1999.
DOI : 10.1023/A:1008382309369

L. Ingber, Adaptive simulated annealing (ASA) Global Optimization C-code, 1993.

L. Ingber and B. Rosen, Genetic Algorithms and Very Fast Simulated Reannealing: A comparison, Mathematical and Computer Modelling, vol.16, issue.11, pp.87-100, 1992.
DOI : 10.1016/0895-7177(92)90108-W

URL : http://doi.org/10.1016/0895-7177(92)90108-w

J. Jägersküpper, How the (1+1) ES using isotropic mutations minimizes positive definite quadratic forms, Theoretical Computer Science, vol.361, issue.1, pp.38-56, 2006.
DOI : 10.1016/j.tcs.2006.04.004

J. Jägersküpper, Probabilistic runtime analysis of (1+1)-ES using isotropic mutations, Proceedings of the 8th annual conference on Genetic and evolutionary computation, pp.461-468, 2006.

J. Jahn, Introduction to the Theory of Nonlinear Optimization, 1996.
DOI : 10.1007/978-3-662-03271-8

E. T. Jaynes, Where do we stand on maximum entropy? In Maximum Entropy Formalism Conference, Massachusetts Institute of Technology, 1978.

M. Jebalia and A. Auger, Log-Linear Convergence of the Scale-Invariant (??/?? w ,??)-ES and Optimal ?? for Intermediate Recombination for Large Population Sizes, PPSN (1), pp.52-62, 2010.
DOI : 10.1007/978-3-642-15844-5_6

URL : https://hal.archives-ouvertes.fr/inria-00494478

Y. Jin, A comprehensive survey of fitness approximation in evolutionary computation, Soft Computing, vol.9, issue.1, pp.3-12, 2005.
DOI : 10.1007/s00500-003-0328-5

C. T. Kelley, Implicit filtering. Number 23 in Software Environments and Tools, SIAM, 2011.
DOI : 10.1137/1.9781611971903

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

B. L. Kennett, M. S. Sambridge, and P. R. Williamson, Subspace methods for large inverse problems with multiple parameter classes, Geophysical Journal International, vol.94, issue.2, pp.237-247, 1988.
DOI : 10.1111/j.1365-246X.1988.tb05898.x

S. Kern, N. Hansen, and P. Koumoutsakos, Local Meta-models for Optimization Using Evolution Strategies, Parallel Problem Solving from Nature -PPSN IX, pp.939-948
DOI : 10.1007/11844297_95

S. Kim and D. Zhang, Convergence properties of direct search methods for stochastic optimization, Proceedings of the 2010 Winter Simulation Conference, pp.1003-1011, 2010.
DOI : 10.1109/WSC.2010.5679089

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

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

T. G. Kolda, R. M. Lewis, and V. Torczon, A generating set direct search augmented lagrangian algorithm for optimization with a combination of general and linear constraints, 2006.

T. G. Kolda, R. M. Lewis, and V. Torczon, Stationarity Results for Generating Set Search for Linearly Constrained Optimization, SIAM Journal on Optimization, vol.17, issue.4, pp.943-968, 2006.
DOI : 10.1137/S1052623403433638

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

S. Koziel and Z. Michalewicz, Evolutionary Algorithms, Homomorphous Mappings, and Constrained Parameter Optimization, Evolutionary Computation, vol.26, issue.3, pp.19-44, 1999.
DOI : 10.1162/evco.1996.4.1.1

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

O. Kramer, A Review of Constraint-Handling Techniques for Evolution Strategies, Applied Computational Intelligence and Soft Computing, vol.43, issue.4, pp.1-11, 2010.
DOI : 10.1016/S0166-3615(99)00046-9

R. Lago, A study on block flexible iterative solvers with application to Earth imaging problem in geophysics, 2013.

G. Lambaré, Stereotomography, GEOPHYSICS, vol.73, issue.5, pp.25-34, 2008.
DOI : 10.1190/1.2952039

J. Larson and S. C. Billups, Stochastic derivative-free optimization using a trust region framework, Computational Optimization and Applications, vol.37, issue.3, 2014.
DOI : 10.1007/s10589-016-9827-z

L. Digabel, Algorithm 909, ACM Transactions on Mathematical Software, vol.37, issue.4, pp.1-15, 2011.
DOI : 10.1145/1916461.1916468

R. M. Lewis and V. Torczon, Pattern Search Methods for Linearly Constrained Minimization, SIAM Journal on Optimization, vol.10, issue.3, pp.917-941, 2000.
DOI : 10.1137/S1052623497331373

R. M. Lewis and V. Torczon, A Globally Convergent Augmented Lagrangian Pattern Search Algorithm for Optimization with General Constraints and Simple Bounds, SIAM Journal on Optimization, vol.12, issue.4, pp.1075-1089, 2002.
DOI : 10.1137/S1052623498339727

M. Locatelli, A note on the Griewank test function, Journal of Global Optimization, vol.25, issue.2, pp.169-174, 2003.
DOI : 10.1023/A:1021956306041

S. Lucidi, M. Sciandrone, and P. Tseng, Objective-derivative-free methods for constrained optimization, Mathematical Programming, vol.92, issue.1, pp.37-59, 1999.
DOI : 10.1007/s101070100266

J. Matyas, Random optimization. Automation and remote control, pp.244-251, 1965.

Z. Michalewicz and M. Schoenauer, Evolutionary Algorithms for Constrained Parameter Optimization Problems, Evolutionary Computation, vol.13, issue.1, pp.1-32, 1996.
DOI : 10.1162/evco.1996.4.1.1

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

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

W. A. Mulder and R. E. Plessix, Exploring some issues in acoustic full waveform inversion, Geophysical Prospecting, vol.52, issue.6, pp.827-841, 2008.
DOI : 10.1111/j.1365-2478.2008.00708.x

O. M. Nabi and L. Xiaodong, A comparative study of CMA-ES on large scale global optimisation, Australasian Conference on Artificial Intelligence, pp.303-312, 2010.

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

Y. Nesterov, Random Gradient-Free Minimization of Convex Functions, Foundations of Computational Mathematics, vol.66, issue.2, 2011.
DOI : 10.1007/s10208-015-9296-2

J. Nocedal and S. J. Wright, Numerical optimization. Springer series in operations research and financial engineering, 2006.

G. Nolet, Seismic Tomography: With Applications in Global Seismology and Exploration Geophysics, 1987.

D. W. Oldenburg, P. R. Mcgillivray, and R. G. Ellis, Generalized Subspace Methods For Large-Scale Inverse Problems, Geophysical Journal International, vol.114, issue.1, pp.12-20, 1993.
DOI : 10.1111/j.1365-246X.1993.tb01462.x

S. Operto, J. Virieux, P. Amestoy, J. Excellent, L. Giraud et al., 3D finite-difference frequency-domain modeling of visco-acoustic wave propagation using a massively parallel direct solver: A feasibility study, GEOPHYSICS, vol.72, issue.5, pp.72-195, 2007.
DOI : 10.1190/1.2759835

URL : https://hal.archives-ouvertes.fr/insu-00355256

S. Operto, J. Virieux, J. X. Dessa, and G. Pascal, Crustal seismic imaging from multifold ocean bottom seismometer data by frequency domain full waveform tomography: Application to the eastern Nankai trough, Journal of Geophysical Research, vol.108, issue.B4, pp.1032-1056, 2006.
DOI : 10.1029/2005JB003835

URL : https://hal.archives-ouvertes.fr/insu-00355209

X. Pinel, A perturbed two-level preconditioner for the solution of three-dimensional heterogeneous Helmholtz problems with applications to Geophysics, CERFACS and INPT, 2010.

R. E. Plessix, A review of the adjoint-state method for computing the gradient of a functional with geophysical applications, Geophysical Journal International, vol.167, issue.2, pp.495-503, 2006.
DOI : 10.1111/j.1365-246X.2006.02978.x

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, 2004.
DOI : 10.1007/0-387-30065-1_16

G. R. Pratt and M. H. Worthington, INVERSE THEORY APPLIED TO MULTI-SOURCE CROSS-HOLE TOMOGRAPHY.. PART 1: ACOUSTIC WAVE-EQUATION METHOD1, Geophysical Prospecting, vol.1, issue.1, pp.287-310, 1990.
DOI : 10.1190/1.1442237

R. G. Pratt, Seismic waveform inversion in the frequency domain, Part 1: Theory and verification in a physical scale model, GEOPHYSICS, vol.64, issue.3, pp.888-901, 1999.
DOI : 10.1190/1.1444597

C. Ravaut, S. Operto, L. Improta, J. Virieux, A. Herrero et al., Multiscale imaging of complex structures from multifold wide-aperture seismic data by frequency-domain full-waveform tomography: application to a thrust belt, Geophysical Journal International, vol.159, issue.3, pp.1032-1056, 2004.
DOI : 10.1111/j.1365-246X.2004.02442.x

URL : https://hal.archives-ouvertes.fr/hal-00407340

I. Rechenberg, Evolutionsstrategie: Optimierung technischer systeme nach prinzipien der biologischen evolution. Frommann-Holzboog, 1973.

R. G. Reynolds, Z. Michalewicz, and M. J. Cavaretta, Using cultural algorithms for constraint handling in GENOCOP, Evolutionary Programming, pp.289-305, 1995.

J. T. Richardson, M. R. Palmer, G. E. Liepins, and M. Hilliard, Some guidelines for genetic algorithms with penalty functions, Proceedings of the third international conference on Genetic algorithms, pp.191-197, 1989.

L. Rios and N. Sahinidis, Derivative-free optimization: a review of algorithms and comparison of software implementations, Journal of Global Optimization, vol.18, issue.3, pp.1247-1293, 2013.
DOI : 10.1007/s10898-012-9951-y

M. Robbé and M. Sadkane, Exact and inexact breakdowns in the block GMRES method, Linear Algebra and its Applications, vol.419, issue.1, pp.265-285, 2006.
DOI : 10.1016/j.laa.2006.04.018

T. P. Runarsson, X. Yao, E. K. Burke, J. A. Lozano, J. Smith et al., Constrained Evolutionary Optimization by Approximate Ranking and Surrogate Models, Lecture Notes in Computer Science, vol.3242, pp.401-410, 2004.
DOI : 10.1007/978-3-540-30217-9_41

Y. Saad, Iterative Methods for Sparse Linear Systems, Second Edition, Society for Industrial and Applied Mathematics, 2003.

K. Scheinberg and P. L. Toint, Self-Correcting Geometry in Model-Based Algorithms for Derivative-Free Unconstrained Optimization, SIAM Journal on Optimization, vol.20, issue.6, pp.3512-3532, 2010.
DOI : 10.1137/090748536

H. Schwefel, Evolutionsstrategie und numerische optimierung, 1975.

H. P. Schwefel, Evolution and optimum seeking: The sixth generation, 1993.

C. Shin and Y. H. Cha, Waveform inversion in the Laplace domain, Geophysical Journal International, vol.173, issue.3, pp.922-931, 2008.
DOI : 10.1111/j.1365-246X.2008.03768.x

C. Shin and W. Ha, A comparison between the behavior of objective functions for waveform inversion in the frequency and Laplace domains, GEOPHYSICS, vol.73, issue.5, pp.119-133, 2008.
DOI : 10.1190/1.2953978

C. Shin and W. Ha, Laplace-domain full-waveform inversion of seismic data lacking lowfrequency information, Geophysics, vol.77, issue.5, pp.199-206, 2012.

L. Sirgue, The Importance of Low Frequency and Large Offset in Waveform Inversion, 68th EAGE Conference and Exhibition incorporating SPE EUROPEC 2006, 2006.
DOI : 10.3997/2214-4609.201402146

L. Sirgue and R. G. Pratt, Efficient waveform inversion and imaging: A strategy for selecting temporal frequencies, GEOPHYSICS, vol.69, issue.1, p.69
DOI : 10.1190/1.1649391

J. Skilling and R. K. Bryan, Maximum entropy image reconstruction: general algorithm, Monthly Notices of the Royal Astronomical Society, vol.211, issue.1, pp.111-124, 1984.
DOI : 10.1093/mnras/211.1.111

J. C. Spall, Introduction to stochastic search and optimization: Estimation, simulation, and control, 2003.
DOI : 10.1002/0471722138

R. Storn and K. Price, Differential evolution &ndash; a simple and efficient heuristic for global optimization over continuous spaces, Journal of Global Optimization, vol.11, issue.4, pp.341-359, 1997.
DOI : 10.1023/A:1008202821328

G. Strang, The Discrete Cosine Transform, SIAM Review, vol.41, issue.1, pp.135-147, 1999.
DOI : 10.1137/S0036144598336745

A. Tarantola, Inverse problem theory and methods for model parameter estimation. Siam, 2005.

C. Tomasi and R. Manduchi, Bilateral filtering for gray and color images, Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271)
DOI : 10.1109/ICCV.1998.710815

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

A. I. 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

A. I. Vaz and L. N. Vicente, PSwarm: a hybrid solver for linearly constrained global derivative-free optimization, Optimization Methods and Software, vol.24, issue.4-5, pp.669-685, 2009.
DOI : 10.1080/10556780902909948

L. N. Vicente and A. L. Custódio, Analysis of direct searches for discontinuous functions, Mathematical Programming, vol.7, issue.1-2, pp.299-325, 2012.
DOI : 10.1007/s10107-010-0429-8

J. Virieux and S. Operto, An overview of full-waveform inversion in exploration geophysics, GEOPHYSICS, vol.74, issue.6, pp.1-26, 2009.
DOI : 10.1190/1.3238367

URL : https://hal.archives-ouvertes.fr/hal-00457989

S. M. Wild and C. A. Shoemaker, Global Convergence of Radial Basis Function Trust-Region Algorithms for Derivative-Free Optimization, SIAM Review, vol.55, issue.2, pp.349-371, 2013.
DOI : 10.1137/120902434

G. Yin, G. Rudolph, and H. P. Schwefel, Analyzing the (1, ??) Evolution Strategy via Stochastic Approximation Methods, Evolutionary Computation, vol.47, issue.4, pp.473-489, 1995.
DOI : 10.1109/TAC.1977.1101561

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

Y. Zhang and L. Gao, On Numerical Solution of the Maximum Volume Ellipsoid Problem, SIAM Journal on Optimization, vol.14, issue.1, pp.53-76, 2003.
DOI : 10.1137/S1052623401397230