E. Audze, P. Audze, and V. Eglais, New approach for planning out of experiments. Problems of Dynamics and Strengths, pp.104-107, 1977.

. Auer, A learning rule for very simple universal approximators consisting of a single layer of perceptrons, Neural Networks, vol.21, issue.5, 2005.
DOI : 10.1016/j.neunet.2007.12.036

O. Babuska, I. Babuska, and J. T. Oden, Verification and validation in computational engineering and science: basic concepts, Computer Methods in Applied Mechanics and Engineering, vol.193, issue.36-38, pp.4057-4066, 2004.
DOI : 10.1016/j.cma.2004.03.002

. Ba?ant, . Caner, Z. Ba?ant, and F. Caner, Microplane Model M5 with Kinematic and Static Constraints for Concrete Fracture and Anelasticity. I: Theory, Journal of Engineering Mechanics, vol.131, issue.1, pp.31-40, 2005.
DOI : 10.1061/(ASCE)0733-9399(2005)131:1(31)

. Ba?ant, Microplane Model M4 for Concrete. I: Formulation with Work-Conjugate Deviatoric Stress, Journal of Engineering Mechanics, vol.126, issue.9, pp.944-953954, 2000.
DOI : 10.1061/(ASCE)0733-9399(2000)126:9(944)

. Brancherie, D. Ibrahimbegovic-]-brancherie, and A. Ibrahimbegovic, Novel anisotropic continuum-discrete damage model capable of representing localized failure. part i: theoretic formulation and numerical implementation, Computers & Structures, 2007.

. Breitkopf, Efficient optimization strategy using hermite diffuse approximation, Proceedings of Fifth World Congress on Computational Mechanics, 2002.

E. Cantú-paz-cantú-paz, Efficient and Accurate Parallel Genetic Algorithms, 2001.
DOI : 10.1007/978-1-4615-4369-5

C. , L. Chen, B. Liu, and J. , Experimental study on ae characteristics of three-point-bending concrete beams, Cement and Concrete Research, vol.34, pp.391-397, 2004.

C. A. Coello, CONSTRAINT-HANDLING USING AN EVOLUTIONARY MULTIOBJECTIVE OPTIMIZATION TECHNIQUE, Civil Engineering and Environmental Systems, vol.26, issue.4, pp.319-346, 2000.
DOI : 10.1162/evco.1994.2.3.221

C. A. Coello, List of references on evolutionary multiobjective optimization, 2004.

. Drchal, Using a genetic algorithm for optimizing synaptic weights of neural networks, CTU Report, vol.7, issue.1, pp.161-172, 2003.

. Fairbairn, Determination of probabilistic parameters of concrete: solving the inverse problem by using artificial neural networks, Computers & Structures, vol.78, issue.1-3, pp.1-3497, 2000.
DOI : 10.1016/S0045-7949(00)00073-0

Y. Furukawa, R. Furukawa, and G. Yagawa, INELASTIC CONSTITUTIVE PARAMETER IDENTIFICATION USING AN EVOLUTIONARY ALGORITHM WITH CONTINUOUS INDIVIDUALS, International Journal for Numerical Methods in Engineering, vol.10, issue.1, pp.1071-1090, 1997.
DOI : 10.1002/(SICI)1097-0207(19970330)40:6<1071::AID-NME99>3.0.CO;2-8

D. Goldberg, Genetic Algorithms in Search, Optimization and Machine Learning, 1989.

. González, Multidisciplinary aircraft conceptual design and optimisation using a robust evolutionary technique, 2004.

J. Grefenstette, Genetic algorithms and their applications, Proceedings of the Second International Conference on Genetic Algorithms and their Applications, 1987.

. Halgamuge, Fast perceptron learning by fuzzy controlled dynamic adaption of network parameters, Fuzzy Systems in Computer Science, pp.129-139, 1994.

. Hartman, Layered Neural Networks with Gaussian Hidden Units as Universal Approximations, Neural Computation, vol.1, issue.2, pp.210-215, 1990.
DOI : 10.1162/neco.1989.1.2.281

S. Haykin, Neural Networks: A Comprehensive Foundation, 1998.

. Hertz, An Introduction to the Theory of Neural Computation, 1991.

J. H. Holland, Adaptation in Natural and Artificial Systems, 1975.

J. J. Hopfield, Neural networks and physical systems with emergent collective computational abilities, Proc. of the National Academy of Science, pp.2554-2558, 1982.

W. Hrstka and O. Hrstka, Homepage of SADE

K. Hrstka, O. Hrstka, and A. Ku?erová, Searching for optimization method on multidimensional real domains, Contributions to Mechanics of Materials and Structures, pp.87-104, 2000.

K. Hrstka, O. Hrstka, and A. Ku?erová, Improvements of real coded genetic algorithms based on differential operators preventing the premature convergence Advances in Engineering Software, pp.3-4237, 2004.

. Hrstka, A competitive comparison of different types of evolutionary algorithms, Computers & Structures, vol.81, issue.18-19, pp.18-191979, 2003.
DOI : 10.1016/S0045-7949(03)00217-7

. Iacono, Estimation of model parameters in nonlocal damage theories by inverse analysis techniques, Computer Methods in Applied Mechanics and Engineering, vol.195, issue.52, pp.1957211-7222, 2006.
DOI : 10.1016/j.cma.2004.12.033

A. Ibrahimbegovi´cibrahimbegovi´c, Stress resultant geometrically nonlinear shell theory with drilling rotations???Part I. A consistent formulation, Computer Methods in Applied Mechanics and Engineering, vol.118, issue.3-4, pp.265-284, 1994.
DOI : 10.1016/0045-7825(94)90003-5

A. Ibrahimbegovi´cibrahimbegovi´c, Finite element implementation of reissner's geometrically nonlinear beam theory: three dimensional curved beam finite elements, Comput. Methods Appl. Eng, vol.122, pp.10-26, 1995.

A. Ibrahimbegovic, Mécanique non linéaire des solides déformables : Formulation théorique et résolution numérique parélémentspar´paréléments finis, 2006.

F. Ibrahimbegovi´cibrahimbegovi´c, A. Ibrahimbegovi´cibrahimbegovi´c, and F. Frey, Finite element analysis of linear and non-linear planar deformations of elastic initially curved beams, International Journal for Numerical Methods in Engineering, vol.97, issue.19, pp.3239-3258, 1993.
DOI : 10.1002/nme.1620361903

. Ibrahimbegovic, A variational formulation of shallow shells, editor, Finite elements in the 1990's, pp.68-79, 1991.

. Ibrahimbegovic, Shape optimization of two???phase inelastic material with microstructure, Engineering Computations, vol.22, issue.5/6, pp.605-645, 2005.
DOI : 10.1108/02644400510603032

. Ibrahimbegovi´cibrahimbegovi´c, Optimal design and optimal control of structures undergoing finite rotations and elastic deformations, International Journal for Numerical Methods in Engineering, issue.14, pp.612428-2460, 2004.

M. Ibrahimbegovi´cibrahimbegovi´c, A. Ibrahimbegovi´cibrahimbegovi´c, and S. Mamouri, On rigid components and joint constraints in nonlinear dynamics of flexible multibody systems employing 3D geometrically exact beam model, Computer Methods in Applied Mechanics and Engineering, vol.188, issue.4, pp.805-831, 2000.
DOI : 10.1016/S0045-7825(99)00363-1

C. Iman, R. L. Iman, and W. Conover, Small sample sensitivity analysis techniques for computer models, with an application to risk assessment, Communications in Statistics -Theory and Methods, issue.17, pp.91749-1842, 1980.

L. Ingber, Simulated annealing: Practice versus theory, Mathematical and Computer Modelling, vol.18, issue.11, pp.29-57, 1993.
DOI : 10.1016/0895-7177(93)90204-C
URL : http://doi.org/10.1016/0895-7177(93)90204-c

[. J. N?me?ek, ]. J. Bittnar, P. N?me?ek, B. P. Padev?t, and Z. Bittnar, Effect of transversal reinforcement in normal and high strength concrete columns, Materials and Structures, vol.23, issue.12, pp.38665-671, 2005.
DOI : 10.1007/BF02484311

[. J. N?me?ek, ]. J. Bittnar, B. N?me?ek, D. R. Patzák, and Z. Bittnar, Microplane models: computational aspects and proposed parallel algorithm, Computers & Structures, vol.80, issue.27-30, pp.27-302099, 2002.
DOI : 10.1016/S0045-7949(02)00242-0

Y. Jin, A comprehensive survey of fitness approximation in evolutionary computation, Soft Computing, vol.9, issue.1, pp.3-12, 2003.
DOI : 10.1007/s00500-003-0328-5

. Jirásek, . Ba?ant, M. E. Jirásek, and . Ba?ant, Inelastic Analysis of Structures, Z. P, 2001.

. Johnson, 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

I. T. Jolliffe, Principal Component Analysis, 2002.
DOI : 10.1007/978-1-4757-1904-8

G. M. Karakasis and K. C. Giannakoglou, On the use of surrogate evaluation models in multi-objective evolutionary algorithms, 2004.

. Ker?ner, Stochastic nonlinear analysis of concrete structures -Part II: Application to fiber-reinforced concrete facade panels, Applications of Statistics and Probability in Civil Engineering: Proceedings of the 10th International Conference, 2007.

T. Kohonen, Self-organized formation of topologically correct feature maps, Biological Cybernetics, vol.13, issue.1, pp.59-69, 1982.
DOI : 10.1007/BF00337288

J. R. Koza, Genetic programming as a means for programming computers by natural selection, Statistics and Computing, vol.4, issue.2, 1992.
DOI : 10.1007/BF00175355

. Kucerova, Novel anisotropic continuum???discrete damage model capable of representing localized failure of massive structures, Engineering Computations, vol.26, issue.1/2, 2007.
DOI : 10.1108/02644400910924834

A. Ku?erová, Optimisation de forme et contrle de chargement des structures elastique soumis de rotations finis en utilisant les algorithmes gntiques, 2003.

. Ku?erová, Material parameter identification for damage models with cracks, Proceedings of the Eighth International Conference on Computational Structures Technology, p.on CD?ROM, 2006.

. Ku?erová, Large black-box functions optimization using radial basis function networks, Proceedings of Eighth International conference on the Application of Artificial Intelligence to Civil, Structural and Environmental Engineering, p.on CD?ROM, 2005.

. Ku?erová, Back analysis of microplane model parameters using soft computing methods, CAMES: Computer Assisted Mechanics and Engineering Sciences, vol.14, issue.2, pp.219-242, 2007.

C. Le, Backpropagation applied to handwritten zip code recognition, Neural Computation, vol.1, issue.4, pp.541-551, 1989.

. Lee, . Hajela, J. Lee, and P. Hajela, Application of classifier systems in improving response surface based approximations for design optimization, Computers & Structures, vol.79, issue.3, pp.333-344, 2001.
DOI : 10.1016/S0045-7949(00)00132-2

N. Lehk´ylehk´y, D. Lehk´ylehk´y, and D. Novák, Probabilistic inverse analysis: Random material parameters of reinforced concrete frame, Ninth International Conference on Engineering Applications of Neural Networks, EAAN2005, pp.147-154, 2005.

D. Luenberger, Linear and nonlinear programming, 1984.
DOI : 10.1007/978-3-319-18842-3

S. W. Mahfoud, A comparison of parallel and sequential niching methods, Proceedings of the Sixth International Conference on Genetic Algorithms, pp.136-143, 1995.

S. W. Mahfoud, Niching methods for genetic algorithms, 1995.

R. Mahnken, Encyclopedia of Computational Mechanics Part 2. Solids and Structures, chapter Identification of Material Parameters for Constitutive Equations, 2004.

. Mahnken, R. Stein-]-mahnken, and E. Stein, Parameter identification for viscoplastic models based on analytical derivatives of a least-squares functional and stability investigations, International Journal of Plasticity, vol.12, issue.4, pp.451-479, 1996.
DOI : 10.1016/S0749-6419(95)00016-X

. Maier, Inverse Analyses in Fracture Mechanics, International Journal of Fracture, vol.70, issue.3, pp.47-73, 2006.
DOI : 10.1007/s10704-006-7153-7

G. Matheron, Principles of geostatistics, Economic Geology, vol.58, issue.8, pp.1246-66, 1963.
DOI : 10.2113/gsecongeo.58.8.1246

. Mckay, A comparison of three methods for selecting values of input variables in the analysis of output from a computer code, Technometrics, vol.21, pp.239-245, 1979.

Z. Michalewicz, Genetic Algorithms + Data Structures = Evolution Programs, 1999.
DOI : 10.1007/978-3-662-02830-8

K. Miettinen, Nonlinear Multiobjective Optimization, 1999.
DOI : 10.1007/978-1-4615-5563-6

D. C. Montgomery, Design and Analysis of Experiments, 2005.

M. Myers, R. H. Myers, and D. C. Montgomery, Response surface methodology: Process and Product Optimization Using Designed Experiments, 1995.

. Nakayama, Approximate optimization using computational intelligence and its application to reinforcement of cablestayed bridges, 2004.

. Narazaki, H. Narazaki, and A. L. Ralescu, A synthesis method for multi-layered neural network using fuzzy sets, IJCAI-91: Workshop on Fuzzy Logic in Artificial Intelligence, pp.54-66, 1991.

L. Novák, D. Novák, and D. Lehk´ylehk´y, ANN inverse analysis based on stochastic small-sample training set simulation, Engineering Applications of Artificial Intelligence, vol.19, issue.7, pp.731-740, 2006.
DOI : 10.1016/j.engappai.2006.05.003

. Novák, Stochastic nonlinear analysis of concrete structures -Part I: From simulation of experiment and parameter identification to reliability assessment, Kanda, Takada, and Furuta Applications of Statistics and Probability in Civil Engineering: Proceedings of the 10th International Conference, 2007.

. Novák, Small-sample probabilistic assessment -software FREET, Proceedings of 9 th International Conference on Applications of Statistic and Prabability in Civil Engineering -ICASP 9, pp.91-96, 2003.

B. N?me?ek, J. N?me?ek, and Z. Bittnar, Experimental investigation and numerical simulation of post-peak behavior and size effect of reinforced concrete columns, Materials and Structures, vol.91, issue.12, pp.37161-169, 2004.
DOI : 10.1007/BF02481615

. Park, . Sandberg, J. Park, and I. W. Sandberg, Universal Approximation Using Radial-Basis-Function Networks, Neural Computation, vol.2, issue.2, pp.246-257, 1991.
DOI : 10.1109/35.41401

. Park, . Sandberg, J. Park, and I. W. Sandberg, Approximation and Radial-Basis-Function Networks, Neural Computation, vol.2, issue.2, pp.305-316, 1993.
DOI : 10.1162/neco.1991.3.2.246

. Patzák and B. Www-]-patzák, Homepage of OOFEM

B. Patzák, B. Patzák, and Z. Bittnar, Design of object oriented finite element code Advances in Engineering Software, pp.10-11759, 2001.

. Pichler, Back analysis of model parameters in geotechnical engineering by means of soft computing, International Journal for Numerical Methods in Engineering, vol.27, issue.14, pp.571943-1978, 2003.
DOI : 10.1002/nme.740

Z. Pyrz, M. Pyrz, and F. Zairi, Identification of viscoplastic parameters of phenomenological constitutive equations for polymers by deterministic and evolutionary approach, Modelling and Simulation in Materials Science and Engineering, vol.15, issue.2, pp.85-103, 2007.
DOI : 10.1088/0965-0393/15/2/006
URL : https://hal.archives-ouvertes.fr/hal-00192344

D. Quagliarella, Airfoil design using Navier-Stokes equations and an asymmetric multi-objective genetic algorithm, Evolutionary Methods for Design, Optimization and Control: Applications to Industrial and Societal Problems, 2003.

. Queipo, Surrogate-based analysis and optimization, Progress in Aerospace Sciences, pp.1-28, 2005.
DOI : 10.1016/j.paerosci.2005.02.001

. Rafiq, . Southcombe, M. Y. Rafiq, and C. Southcombe, Genetic algorithms in optimal design and detailing of reinforced concrete biaxial columns supported by a declarative approach for capacity checking, Computers & Structures, vol.69, issue.4, pp.443-457, 1998.
DOI : 10.1016/S0045-7949(98)00108-4

. Rajasekaran, Artificial fuzzy neural networks in civil engineering, Computers & Structures, vol.61, issue.2, pp.61291-302, 1996.
DOI : 10.1016/0045-7949(96)00044-2

. Saastamoinen, Waveform detection with RBF network ??? Application to automated EEG analysis, Neurocomputing, vol.20, issue.1-3, pp.1-13, 1998.
DOI : 10.1016/S0925-2312(98)00005-8

. Sacks, Designs for Computer Experiments, Technometrics, vol.15, issue.18, pp.15-25, 1989.
DOI : 10.1080/00401706.1989.10488474

. Shewry, . Wynn, M. Shewry, and H. Wynn, Maximum entropy sampling, Journal of Applied Statistics, vol.14, issue.2, pp.165-170, 1987.
DOI : 10.2307/2987990

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

R. Storn, On the usage of differential evolution for function optimization, Proceedings of North American Fuzzy Information Processing, pp.519-523, 1996.
DOI : 10.1109/NAFIPS.1996.534789

. Storn and R. Www-]-storn, WWW) Homepage of Differential Evolution

P. Storn, R. Storn, and K. Price, Differential Evolution : A simple and efficient adaptive scheme for global optimization over continuous spaces, 1995.

Y. Toropov, V. Toropov, and F. Yoshida, Parameter identification of materials and structures, chapter Application of advanced optimization techniques to parameter and damage identification problems, pp.177-263, 2005.

. Toropov, Generation of extended unifrom latin hypercube design of experiments, Proceedings of the Ninth International Conference of the Application of Artificial Intelligence to Civil, Structural and environmental Engineering, 2007.

L. H. Tsoukalas and R. E. Uhrig, Fuzzy and neural aproaches in engineering, 1997.

. Valenta, Construction of a statistically equivalent periodic unit cell for an asphalt mixture, Proceedings of The Eleventh International conference on Civil, Structural and Environmental Engineering Computing, p.on CD?ROM, 2007.

E. Varcol, C. M. Varcol, and T. M. Emmerich, Metamodel-assisted evolution strategies applied in electromagnetic compatibility design, Evolutionary and Eterministic Methods for Design, Optimization and Control with Applications to Industrial and Societal Problems EUROGEN 2005. FLM, 2005.

R. V. Vidal, Applied Simulated Annealing, of Lecture Notes in Economics and Mathematical Systems, 1993.
DOI : 10.1007/978-3-642-46787-5

P. Villon, ContributionàContribution`Contributionà l'optimisation, 1991.

. Wang, Parallel evolutionary algorithms for optimization problems in aerospace engineering, Journal of Computational and Applied Mathematics, vol.149, issue.1, pp.155-169, 2002.
DOI : 10.1016/S0377-0427(02)00527-7

. Waszczyszyn, Z. Ziemianski-]-waszczyszyn, and L. Ziemianski, Parameter identification of materials and structures, chapter Neural networks in the identification analysis of structural mechanics problems, pp.265-340, 2005.

. Waszczyszyn, Z. Ziemia´nskiziemia´nski-]-waszczyszyn, and L. Ziemia´nskiziemia´nski, Neurocomputing in the analysis of selected inverse problems of mechanics of structures and materials, Computer Assisted Mechanics and Engineering Sciences, vol.13, issue.1, pp.125-159, 2006.

. Weigend, A. S. Gershenfeld-]-weigend, and N. A. Gershenfeld, Time Series Prediction: Forecasting the Future and Understanding the Past, 1994.

S. Christensen, Genetic and evolutionary computation conference, Proceedings of the 2007 GECCO conference companion on Genetic and evolutionary computation, pp.3765-3791, 2007.

O. Yagawa, G. Yagawa, H. Okuda, and K. Hrstka, Neural networks in computational mechanics. CIMNE. Appendix A LIST OF FUNCTIONS APPLIED FOR GENETIC ALGORITHMS TESTING The following set of mathematical test functions was taken from the article [Andre et al., 2000] and the same set of functions was also applied for the comparison of genetic algorithms published in the article, 1996.