. Foretnik, Nurbs demo. geometrie.foretnik.net/files/NURBS-en.swf, pp.70-71, 2010.

]. L. Piegl and W. Tiller, The nurbs book. Monographs in visual communication, 1995.
DOI : 10.1007/978-3-642-59223-2

.. Bibliographie-du-4-e-chapitre, 132 4.5. Discussion des résultats et synthèse 4 Minimization of functions having Lipschitz continuous first partial derivatives, Pacific J. Math, vol.16, issue.1, pp.1-3, 1966.

]. D. Benoist, Y. Tourbier, and S. Germain-tourbier, Plans d'expériences : construction et analyse, pp.9-116, 1994.

]. J. Culioli, Introduction à l'optimisation. Ellipses, pp.7-99, 1994.

]. A. Goldstein, On Steepest Descent, Journal of the Society for Industrial and Applied Mathematics Series A Control, vol.3, issue.1, pp.147-151, 1965.
DOI : 10.1137/0303013

R. Hastie-2001-]-trevor-hastie, J. Tibshirani, and . Friedman, The elements of statistical learning, 2001.

]. M. Johnson, L. M. Moore, and D. Ylvisaker, Minimax and maximin distance designs, Journal of Statistical Planning and Inference, vol.26, issue.2, pp.131-148, 1990.
DOI : 10.1016/0378-3758(90)90122-B

]. Jones and T. Oliphant, Pearu Petersonet al. SciPy : Open source scientific tools for Python [Online, pp.2016-2022, 2001.

]. R. Marler and J. S. Arora, Survey of multi-objective optimization methods for engineering. Structural and Multidisciplinary Optimization, pp.369-395, 2004.

]. J. Nocedal and S. J. Wright, Numerical optimization, 2006.
DOI : 10.1007/b98874

F. Pedregosa, G. Varoquaux, A. Gramfort, V. Michel, B. Thirion et al., Scikit-learn : Machine Learning in Python, Journal of Machine Learning Research, vol.12, pp.2825-2830, 2011.
URL : https://hal.archives-ouvertes.fr/hal-00650905

P. Wolfe and . Wolfe, Convergence Conditions for Ascent Methods. II: Some Corrections, SIAM Review, vol.13, issue.2, pp.185-188, 1971.
DOI : 10.1137/1013035

. Bibliographie, M. Howard, R. T. Adelman, and . Haftka, Sensitivity Analysis of Discrete Structural Systems, AIAA Journal, vol.24, issue.5, pp.823-832, 1986.

F. Allaire-2004-]-grégoire-allaire, A. Jouve, and . Toader, Structural optimization using sensitivity analysis and a level-set method, Journal of Computational Physics, vol.194, issue.1, pp.363-393, 2004.
DOI : 10.1016/j.jcp.2003.09.032

. Allaire-2007-]-grégoire-allaire, Conception optimale de structures, pp.11-14, 2007.

]. W. Anderson and V. Venkatakrishnan, Aerodynamic design optimization on unstructured grids with a continuous adjoint formulation, Computers & Fluids, vol.28, issue.4-5, pp.443-480, 1999.
DOI : 10.1016/S0045-7930(98)00041-3

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.211.3496

L. Armijo and . Armijo, Minimization of functions having Lipschitz continuous first partial derivatives, Pacific Journal of Mathematics, vol.16, issue.1, pp.1-3, 1966.
DOI : 10.2140/pjm.1966.16.1

URL : http://projecteuclid.org/download/pdf_1/euclid.pjm/1102995080

]. C. Armstrong, T. T. Robinson, C. Ou, and . Othmer, Linking adjoint sensitivity maps with CAD parameters. Evolutionary and Deterministic Methods for Design, Optimization and Contol, pp.234-239, 2007.

P. Martin, O. Bendsøe, and . Sigmund, Topology optimization : Theory, methods and applications, 2003.

]. D. Benoist, Y. Tourbier, and S. Germain-tourbier, Plans d'expériences : construction et analyse, pp.9-116, 1994.

]. G. Boole, A treatise on the calculus of finite differences, pp.1860-1878, 1860.
DOI : 10.1017/CBO9780511693014

G. Dan and . Cacuci, Sensitivity theory for nonlinear systems. I. Nonlinear functional analysis approach, Journal of Mathematical Physics, vol.22, issue.12, pp.2794-2802, 1981.

]. S. Chen and D. A. Torterelli, Three-dimensional shape optimization with variational geometry Structural optimization, pp.81-94, 1997.
DOI : 10.1007/bf01199226

K. Kyung, K. Choi, and . Chang, A study of design velocity field computation for shape optimal design, Finite Elements in Analysis and Design, vol.15, issue.4, pp.317-341, 1994.

K. Kyung, N. Choi, and . Kim, Structural sensitivity analysis and optimization 1, 2005.

]. J. Culioli, Introduction à l'optimisation. Ellipses, pp.7-99, 1994.

]. J. Dannenhoffer, I. , and R. Haimes, Design Sensitivity Calculations Directly on CAD-based Geometry, 53rd AIAA Aerospace Sciences Meeting, pp.23-65, 1370.
DOI : 10.2514/6.2015-1370

]. C. Dapogny, Shape optimization, level set methods on unstructured meshes and mesh evolution, pp.11-13, 2013.
URL : https://hal.archives-ouvertes.fr/tel-00916224

]. Darcy, Recherches expérimentales relatives au mouvement de l'eau dans les tuyaux, pp.1857-1869, 1857.

S. Michael, K. Floater, and . Hormann, Surface Parameterization : a Tutorial and Survey. Article, 2002.

. Foretnik, Nurbs demo. geometrie.foretnik.net/files/NURBS-en.swf, pp.70-71, 2010.

]. C. Geuzaine and J. F. Remacle, Gmsh: A 3-D finite element mesh generator with built-in pre- and post-processing facilities, International Journal for Numerical Methods in Engineering, vol.69, issue.4, pp.1309-1331, 2009.
DOI : 10.1002/nme.2579

]. A. Goldstein, On Steepest Descent, Journal of the Society for Industrial and Applied Mathematics Series A Control, vol.3, issue.1, pp.147-151, 1965.
DOI : 10.1137/0303013

]. X. Gu and S. T. Yau, Computational conformal geometry, volume 3 of Advanced lectures in mathematics, pp.27-54, 2008.

S. Richard and . Hamilton, Three-manifolds with positive Ricci curvature, J. Differential Geom, vol.17, issue.2, pp.255-306, 1982.

R. Bibliographie-globale-]-trevor-hastie, J. Tibshirani, and . Friedman, The elements of statistical learning, 2001.

]. T. Hughes, J. A. Cottrell, and Y. Bazilevs, Isogeometric analysis: CAD, finite elements, NURBS, exact geometry and mesh refinement, Computer Methods in Applied Mechanics and Engineering, vol.194, issue.39-41, pp.39-41, 2005.
DOI : 10.1016/j.cma.2004.10.008

URL : https://hal.archives-ouvertes.fr/hal-01513346

]. M. Johnson, L. M. Moore, and D. Ylvisaker, Minimax and maximin distance designs, Journal of Statistical Planning and Inference, vol.26, issue.2, pp.131-148, 1990.
DOI : 10.1016/0378-3758(90)90122-B

]. Jones and T. Oliphant, Pearu Petersonet al. SciPy : Open source scientific tools for Python [Online, pp.2016-2022, 2001.

S. Julisson, Optimisation de formes de coques minces pour des géométries complexes, 2016.

]. J. Keller, Inverse Problems, The American Mathematical Monthly, vol.83, issue.2, pp.107-118, 1976.
DOI : 10.2307/2976988

T. Carl and . Kelley, Iterative methods for optimization, Siam, vol.18, 1999.

L. Bruno and J. Mallet, Paramétrisation des surfaces triangulées. Revue internationale de CFAO et d'informatique graphique, pp.25-42, 2000.

]. T. Lindby and J. L. Santos, Shape optimization of three-dimensional shell structures with the shape parametrization of a CAD system Structural optimization, pp.126-133, 1999.

]. R. Marler and J. S. Arora, Survey of multi-objective optimization methods for engineering. Structural and Multidisciplinary Optimization, pp.369-395, 2004.

]. O. Moos, F. Klimetzek, and R. Rossmann, Bionic Optimization of Air-Guiding Systems, SAE Technical Paper Series, 2004.
DOI : 10.4271/2004-01-1377

]. J. Nocedal and S. J. Wright, Numerical optimization, 2006.
DOI : 10.1007/b98874

S. Osher and J. A. Sethian, Fronts propagating with curvature-dependent speed: Algorithms based on Hamilton-Jacobi formulations, Journal of Computational Physics, vol.79, issue.1, pp.12-49, 1988.
DOI : 10.1016/0021-9991(88)90002-2

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.413.5254

. Bibliographie-globale, Othmer et Th. Grahs. Approaches to fluid dynamic optimization in the car development process, EUROGEN, 2005.

F. Pedregosa, G. Varoquaux, A. Gramfort, V. Michel, B. Thirion et al., Scikit-learn : Machine Learning in Python, Journal of Machine Learning Research, vol.12, pp.2825-2830, 2011.
URL : https://hal.archives-ouvertes.fr/hal-00650905

]. J. Peter, S. Burguburu, and M. Marcelet, Introduction à l'optimisation de forme en aérodynamique et quelques exemples d'application. ONERA, 2006.

]. L. Piegl and W. Tiller, The nurbs book. Monographs in visual communication, 1995.
DOI : 10.1007/978-3-642-59223-2

]. Remacle, C. Geuzaine, G. Compère, and E. Marchandise, High-quality surface remeshing using harmonic maps, International Journal for Numerical Methods in Engineering, vol.3, issue.2, pp.403-425, 2010.
DOI : 10.1002/nme.2824

URL : http://orbi.ulg.ac.be/request-copy/2268/35706/90298/10.ijnme.remacle.reparam.pdf

T. T. Robinson, C. G. Armstrong, H. S. Chua, C. Othmer, and T. Grahs, Optimizing Parameterized CAD Geometries Using Sensitivities Based on Adjoint Functions, Computer-Aided Design and Applications, vol.46, issue.3, pp.253-268, 2012.
DOI : 10.1016/j.cma.2006.05.001

K. Saitou, S. Izui, P. Nishiwaki, and . Shepard, A Survey of Structural Optimization in Mechanical Product Development, Proceedings of the 1968 23rd ACM National Conference, ACM '68, pp.214-226, 1968.
DOI : 10.1115/1.2013290

J. Sokolowski and . Zolesio, Introduction to shape optimization : shape sensitivity analysis. Springer series in computational mathematics, p.66, 1992.

]. M. Staten, S. J. Owen, S. M. Shontz, A. G. Salinger, and T. S. Coffey, A Comparison of Mesh Morphing Methods for 3D Shape Optimization, Proceedings of the 20 th international meshing round-table, pp.293-311, 2011.
DOI : 10.1007/978-3-642-24734-7_16

I. Jukka, J. Toivanen, and . Martikainen, A new method for creating sparse design velocity fields, Computer Methods in Applied Mechanics and Engineering, vol.196, pp.528-537, 2006.

. Vasilopoulos, . Agarwal, . Meyer, C. Robinson, and . Armstrong, LINKING PARAMETRIC CAD WITH ADJOINT SURFACE SENSITIVITIES, Proceedings of the VII European Congress on Computational Methods in Applied Sciences and Engineering (ECCOMAS Congress 2016), pp.2016-2042, 2016.
DOI : 10.7712/100016.2075.6192

]. Xu, W. Jahn, and J. Müller, CAD-based shape optimisation with CFD using a discrete adjoint, International Journal for Numerical Methods in Fluids, vol.15, issue.1, pp.153-168, 2014.
DOI : 10.1002/fld.3844

]. R. Bibliographie-globale, A. Yang, D. T. Lee, and . Mcgeen, Application of basis function concept to practical shape optimization problems Structural optimization, pp.55-63, 1992.