P. J. Angeline, The effects of noise on self-adaptive evolutionary optimization

J. Antonisse, A new interpretation of schema notation that overturns the binary encoding constraint, Proceedings of the 3 rd International Conference on Genetic Algorithms, pp.86-91, 1989.

D. V. Arnold and H. Beyer, Local performance of the (µ/µ i ,?)-es in a noisy environment, Foundations of Genetic Algorithms 6, pp.127-141, 2001.

A. Auger, Contributions théoriques et numériquesnumériquesà l'optimisation continue par algorithmesévolutionnairesalgorithmesévolutionnaires, 2004.

A. Auger, M. Schoenauer, and O. Teytaud, Local and global order 3/2 convergence of a surrogate evolutionary algorithm, Proceedings of the 2005 conference on Genetic and evolutionary computation , GECCO '05, 2004.
DOI : 10.1145/1068009.1068154

T. Bäck, Optimal mutation rates in genetic search, Proceedings of the 5 th International Conference on Genetic Algorithms, pp.2-8, 1993.

T. Bäck, Selective pressure in evolutionary algorithms: a characterization of selection mechanisms, Proceedings of the First IEEE Conference on Evolutionary Computation. IEEE World Congress on Computational Intelligence, pp.57-62, 1994.
DOI : 10.1109/ICEC.1994.350042

T. Bäck, Evolutionary Algorithms in Theory and Practice, 1996.

T. Bäck, M. Schütz, and S. Khuri, A comparative study of a penalty function, a repair heuristic, and stochastic operators with the set-covering problem
DOI : 10.1007/3-540-61108-8_47

S. Baluja, Population-based incremental learning : a method for integrating genetic search based function optimization and competitive learning, 1994.

S. Baluja, An empirical comparison of seven iterative and evolutionary function optimization heuristics, 1995.

W. Banzhaf, P. Nordin, R. E. Keller, and F. D. Francone, Genetic Programming ? An Introduction On the Automatic Evolution of Computer Programs and Its Applications, 1998.

]. S. Benhamida, AlgorithmesÉvolutionnairesAlgorithmes´AlgorithmesÉvolutionnaires : Prise en Compte des Contraintes et Application Réelle, p.29, 2001.

P. J. Bentley, Evolutionary Design by Computers, 1999.
DOI : 10.1007/978-1-4471-0819-1_8
URL : http://arxiv.org/abs/cs/9809049

J. Berthelot, Matériaux Composites : comportement mécanique et analyse des structures, 1999.

H. Beyer, An alternative explanation for the manner in which genetic algorithms operate, Biosystems, vol.41, issue.1, pp.1-15, 1997.
DOI : 10.1016/S0303-2647(96)01657-7

H. Beyer, Mutate large, but inherit small ! On the analysis of mutations in (1, ?)-ES with noisy fitness data, Proceedings of the 5 th Conference on Parallel Problems Solving from Nature, pp.109-118, 1998.

H. Beyer, The Theory of Evolution Strategies, 2001.
DOI : 10.1007/978-3-662-04378-3

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

P. A. Bosman and D. Thierens, Expanding from Discrete to Continuous Estimation of Distribution Algorithms: The ID$$ \mathbb{E} $$A, Proceedings of the 6 th Conference on Parallel Problems Solving from Nature, pp.767-776, 1917.
DOI : 10.1007/3-540-45356-3_75

S. Cahon, N. Melab, E. Talbi, and M. Schoenauer, ParaDisEO-Based Design of Parallel and Distributed Evolutionary Algorithms, Artificial Evolution 03, pp.215-227, 2003.
DOI : 10.1007/978-3-540-24621-3_18
URL : https://hal.archives-ouvertes.fr/inria-00201075

E. Cantu-paz, Efficient and Accurate Parallel Genetic Algorithms, 2000.
DOI : 10.1007/978-1-4615-4369-5

R. Cerf, Une théorie asymptotique des algorithmes génétiques, 1994.

C. D. Chapman and M. J. Jakiela, Genetic Algorithm-Based Structural Topology Design With Compliance and Topology Simplification Considerations, Journal of Mechanical Design, vol.118, issue.1, pp.89-98, 1996.
DOI : 10.1115/1.2826862

C. D. Chapman, K. Saitou, and M. J. Jakiela, Genetic Algorithms as an Approach to Configuration and Topology Design, Journal of Mechanical Design, vol.116, issue.4, pp.1005-1012, 1994.
DOI : 10.1115/1.2919480

P. G. Ciarlet, Three-Dimensional Elasticity. North-Holland, Mathematical Elasticity, vol.I, 1978.
URL : https://hal.archives-ouvertes.fr/hal-01077590

C. A. Coello-coello, D. A. Van-veldhuizen, and G. B. Lamont, Evolutionary Algorithms for Solving Multi-Objective Problems, 2002.
DOI : 10.1007/978-1-4757-5184-0

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

N. J. Cramer, A representation for the adaptive generation of simple sequential programs, Proceedings of the 1 st International Conference on Genetic Algorithms, pp.183-187, 1985.

N. A. Cressie, Statistics for spatial data, 1993.

J. M. Daida, Challenges with verification, repeatability, and meaningful comparison in genetic programming : Gibson's magic, Proceedings of the Genetic and Evolutionary Conference 99, pp.1069-1076, 1999.

L. Davis, Applying adaptive algorithms to epistatic domains, Proc. Intl. Joint Conference on Artificial Intelligence, 1985.

L. Davis, Handbook of Genetic Algorithms, 1991.

K. Deb, Multi-objective optimization using genetic algorithms, 2001.

K. Deb, S. Agrawal, A. Pratab, and T. Meyarivan, A fast elitist nondominated sorting genetic algorithm for multi-objective optimization : Nsga-ii
DOI : 10.1007/3-540-45356-3_83
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.18.4257

K. Deb and H. Beyer, Self-Adaptive Genetic Algorithms with Simulated Binary Crossover, Evolutionary Computation, vol.3, issue.2, 2001.
DOI : 10.1016/0303-2647(95)01534-R
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.36.3285

K. A. Dejong, Are genetic algorithms function optimizers ?, Proceedings of the 2 nd Conference on Parallel Problems Solving from Nature, pp.3-13, 1992.

K. A. Dejong, The Analysis of the Behavior of a Class of Genetic Adaptive Systems, 5140B. (University Microfilms No, pp.76-9381, 1975.

M. Ebner, Evolutionary Design of Objects Using Scene Graphs, Proc. EuroGP, 2003.
DOI : 10.1007/3-540-36599-0_5

A. E. Eiben and J. E. Smith, Introduction to Evolutionary Computing, 2003.

P. Flajolet, P. Zimmerman, and B. Van-cutsem, A calculus for the random generation of labelled combinatorial structures, Theoretical Computer Science, vol.132, issue.1-2, pp.1-35, 1994.
DOI : 10.1016/0304-3975(94)90226-7
URL : https://hal.archives-ouvertes.fr/hal-00917729

D. E. Goldberg, The Design of Innovation : Lessons from and for Competent Genetic Algorithms, 2002.

D. E. Goldberg, K. Deb, and J. H. Clark, Genetic algorithms, noise, and the sizing of populations, 1991.

D. E. Goldberg, B. Korb, and K. Deb, Messy genetic algorithms : Motivations, analysis and first results, Complex Systems, vol.3, pp.493-530, 1989.

D. E. Goldberg, B. Korb, and K. Deb, Messy genetic algorithms revisited : Nonuniform size and scale, Complex Systems, vol.4, pp.415-444, 1990.

D. E. Goldberg and R. E. Smith, Nonstationary function optimization using genetic algorithms with dominance and diploidy, Proceedings of the 2 nd International Conference on Genetic Algorithms, pp.59-68, 1987.

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

J. J. Grefenstette, Optimization of Control Parameters for Genetic Algorithms, IEEE Transactions on Systems, Man, and Cybernetics, vol.16, issue.1, pp.122-128, 1986.
DOI : 10.1109/TSMC.1986.289288

L. Grosset, Optimization of Composite Structures by Estimation of Distribution Algorithms, 2004.

L. Grosset, R. Le-riche, and R. T. Haftka, A double-distribution statistical algorithm for composite laminate optimization. Structural and Multidisciplinary Optimization, pp.49-59, 2006.
URL : https://hal.archives-ouvertes.fr/hal-00407639

F. Gruau, On using syntactic constraints with genetic programming, Advances in Genetic Programming II, pp.377-394, 1996.

H. Hamda, F. Jouve, E. Lutton, M. Schoenauer, and M. Sebag, Compact unstructured representations in evolutionary topological optimum design, Applied Intelligence, vol.16, issue.2, pp.139-155, 2002.
DOI : 10.1023/A:1013666503249

H. Hamda, O. Roudenko, and M. Schoenauer, Multi-Objective Evolutionary Topological Optimum Design, Evolutionary Design and Manufacture, pp.121-132, 2002.
DOI : 10.1007/978-0-85729-345-9_11
URL : https://hal.archives-ouvertes.fr/inria-00000848

H. Hamda and M. Schoenauer, Toward hierarchical representations for evolutionary topological optimum design, memoriam of B. Mantel, 2000.

N. Hansen, S. 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, 2003.
DOI : 10.1162/106365601750190398

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 6 th International Conference on Genetic Algorithms, pp.57-64, 1995.

W. E. Hart, N. Krasnogor, and J. E. Smith, Recent advances in memetic algorithms, Series : Studies in Fuzziness and Soft Computing, 2005.
DOI : 10.1007/3-540-32363-5

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

C. Igel, N. Hansen, and S. Roth, Covariance Matrix Adaptation for Multi-objective Optimization, Evolutionary Computation, vol.15, issue.1, 2006.
DOI : 10.1109/TEVC.2003.810758
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.469.4052

E. Jensen, Topological Structural Design using Genetic Algorithms, 1992.

Y. Jin, M. Olhofer, and B. Sendho, A framework for evolutionary optimization with approximate fitness functions, IEEE Transactions on Evolutionary Computation, vol.6, issue.5, pp.481-494, 2002.

D. Jones, M. Schonlau, and W. Welch, Efficient global optimization of expensive black-box functions, Journal of Global Optimization, vol.13, issue.4, pp.455-492, 1998.
DOI : 10.1023/A:1008306431147

T. Jones, Evolutionary algorithms, fitness landscapes and search, 1995.

K. A. De and . Jong, An analysis of the behavior of a class of genetic adaptative systems, 1975.

K. A. De and . Jong, Evolutionary Computation : a unified approach, 2006.

L. Kallel and M. Schoenauer, Alternative random initialization in genetic algorithms, Proceedings of the 7 th International Conference on Genetic Algorithms, pp.268-275, 1997.

C. Kane, Algorithmes génétiques et Optimisation topologique, 1996.

C. Kane, F. Jouve, and M. Schoenauer, Structural topology optimization in linear and nonlinear elasticity using genetic algorithms, Proceedings of the ASME 21st Design Automation Conference, 1995.

C. Kane and M. Schoenauer, Genetic operators for two-dimensional shape optimization, Artificial Evolution, number 1063 in LNCS, 1995.

C. Kane and M. Schoenauer, Topological optimum design using genetic algorithms, Control and Cybernetics, vol.25, issue.5, pp.1059-1088, 1996.

C. Kane and M. Schoenauer, Optimisation topologique de formes par algorithmes génétiques. Revue Française de Mécanique, pp.237-246, 1997.

S. Kern, N. Hansen, S. Müller, D. Büche, J. Ocenasek et al., Learning probability distributions in continuous evolutionary algorithms ??? a comparative review, Natural Computing, vol.3, issue.1, pp.77-112, 2004.
DOI : 10.1023/B:NACO.0000023416.59689.4e

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

N. Kogiso, L. T. Watson, Z. Gürdal, and R. T. Haftka, Genetic algorithms with local improvement for composite laminate design, Structural Optimization, vol.35, issue.4, pp.207-218, 1994.
DOI : 10.1007/BF01743714

N. Kogiso, L. T. Watson, Z. Gürdal, R. T. Haftka, and S. Nagendra, DESIGN OF COMPOSITE LAMINATES BY A GENETIC ALGORITHM WITH MEMORY, Mechanics of Advanced Materials and Structures, vol.1, issue.1, pp.95-117, 1994.
DOI : 10.1080/10759419408945823

J. R. Koza, Genetic Programming : On the Programming of Computers by means of Natural Evolution, 1992.

J. R. Koza, Genetic Programming II : Automatic Discovery of Reusable Programs, 1994.

J. R. Koza, Genetic Programming III : Automatic Synthesis of Analog Circuits, 1999.

W. B. Langdon and W. Banzhaf, Genetic Programming Bloat without Semantics, Parallel Problem Solving from Nature -PPSN VI 6th International Conference, pp.201-210, 2000.
DOI : 10.1007/3-540-45356-3_20
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.129.6027

P. Larranaga and J. A. Lozano, Estimation of Distribution Algorithms. A New Tool for Evolutionary Computation, 2001.

M. Laumanns, L. Thiele, K. Deb, and E. Zitzler, Archiving with guaranteed convergence and diversity in multi-objective optimization, Proceedings of the Genetic and Evolutionary Conference 2002, pp.39-447, 2002.

R. , L. Riche, and G. Cailletaud, A mixed evolutionary/heuristic approach to shape optimization, International Journal of Numerical Methods in Engineering, vol.41, pp.1463-1484, 1998.
URL : https://hal.archives-ouvertes.fr/emse-00759353

L. Riche and R. T. Haftka, Optimization of laminate stacking sequence for buckling load maximization by genetic algorithm, AIAA Journal, vol.31, issue.5, pp.951-970, 1993.
DOI : 10.2514/3.11710

R. , L. Riche, and R. T. Haftka, Improved genetic algorithm for minimum thickness composite laminate design, Composites Engineering, vol.5, issue.2, pp.143-161, 1995.

R. Le-riche, C. Knopf-lenoir, and R. T. Haftka, A segregated genetic algorithm for constrained structural optimization, Proceedings of the Sixth International Conference on Genetic Algorithms (ICGA95), pp.558-565

S. Lin and B. Kernighan, An Effective Heuristic Algorithm for the Traveling-Salesman Problem, Operations Research, vol.21, issue.2, pp.498-516, 1973.
DOI : 10.1287/opre.21.2.498

S. W. Mahfoud, Niching Methods for Genetic Algorithms, 1995.

S. W. Mahfoud and D. E. Goldberg, Parallel recombinative simulated annealing: A genetic algorithm, Parallel Computing, vol.21, issue.1, pp.1-28, 1995.
DOI : 10.1016/0167-8191(94)00071-H
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.29.4198

W. N. Martin, J. Liening, and J. P. Cohoon, Evolutionary Computation 2 : Advanced Algorithms and Operators, chapter Island (migration) models : evolutionary algorithms based on punctuated equilibria, Inst. of Physics Editor, pp.101-124, 2000.

Z. Michalewicz, Genetic Algorithms + Data Structures = Evolution Programs, 1992.
DOI : 10.1007/978-3-662-02830-8

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

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=10.1.1.13.9279

M. Minoux, Mathematical programming : Theory and Algorithms, 1986.

H. Mühlenbein, The Equation for Response to Selection and Its Use for Prediction, Evolutionary Computation, vol.3, issue.3, pp.303-346, 1998.
DOI : 10.1162/evco.1994.2.4.347

H. Mühlenbein and T. Mahnig, Theoretical aspects of evolutionary computing, chapter Evolutionary algorithms : from recombination to search algorithms, pp.135-174, 2000.

S. Obayashi, Pareto Solutions of Multipoint Design of Supersonic Wings Using Evolutionary Algorithms, Adaptive Computing in Design and Manufacture V, pp.3-15, 2002.
DOI : 10.1007/978-0-85729-345-9_1

J. Paredis, Co-evolutionary constraint satisfaction, Proceedings of the 3 rd Conference on Parallel Problems Solving from Nature, pp.46-55, 1994.
DOI : 10.1007/3-540-58484-6_249

M. Pelikan, D. E. Goldberg, and E. Cantu-paz, Boa : the bayesian optimization algorithm, Proceedings of the Genetic and Evolutionary Conference 1999, pp.525-532, 1999.

L. Riche and R. , Optimization of composite structures by genetic algorithms, 1994.

N. J. Radcliffe, Equivalence class analysis of genetic algorithms, Complex Systems, vol.5, pp.183-203, 1991.

N. J. Radcliffe, Genetic Set Recombination, Foundations of Genetic Algorithms Foundations of Genetic Algorithms 2, pp.203-220, 1993.
DOI : 10.1016/B978-0-08-094832-4.50019-2
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.15.6059

N. J. Radcliffe and P. D. Surry, Fitness Variance of Formae and Performance Prediction, Foundations of Genetic Algorithms 3, pp.51-72, 1995.
DOI : 10.1016/B978-1-55860-356-1.50007-8

A. Ratle, Accelerating the convergence of evolutionary algorithms by fitness landscape approximation, Proceedings of the 5 th Conference on Parallel Problems Solving from Nature, pp.87-96, 1998.
DOI : 10.1007/BFb0056852

A. Ratle and M. Sebag, Genetic Programming and Domain Knowledge: Beyond the Limitations of Grammar-Guided Machine Discovery, Proceedings of the 6 th Conference on Parallel Problems Solving from Nature, pp.211-220, 1917.
DOI : 10.1007/3-540-45356-3_21
URL : https://hal.archives-ouvertes.fr/hal-00116116

A. Ratle and M. Sebag, Grammar-guided genetic programming and dimensional consistency: application to non-parametric identification in mechanics, Applied Soft Computing, vol.1, issue.1, pp.105-118, 2001.
DOI : 10.1016/S1568-4946(01)00009-6
URL : https://hal.archives-ouvertes.fr/hal-00111336

A. Ratle and M. Sebag, Avoiding the Bloat with Stochastic Grammar-Based Genetic Programming, Artificial Evolution'01, pp.254-266, 2002.
DOI : 10.1007/3-540-46033-0_21
URL : https://hal.archives-ouvertes.fr/inria-00001095

I. Rechenberg, Cybernetic solution path of an experimental problem, Royal Aircraft Establishment, 1965.

I. Rechenberg, Evolutionsstrategie : Optimierung technischer System nach Principen der Biologischen Evolution. Frommann-Holzboog, 1973.

C. Reeves and C. Wright, Epistasis in genetic algorithms : an experimental design perspective, Proceedings of the 6 th International Conference on Genetic Algorithms, pp.217-230, 1995.

G. Rudolf, Finite markov chain results in evolutionary computation : A tour d'horizon, Fundamenta Informaticae, vol.35, issue.1-4, pp.67-89, 1998.

F. Schoen, Stochastic techniques for global optimization: A survey of recent advances, Journal of Global Optimization, vol.21, issue.3, pp.207-228, 1990.
DOI : 10.1007/BF00119932

M. Schoenauer, M. Sebag, F. Jouve, B. Lamy, and H. Maitournam, Evolutionary identification of macro-mechanical models, Advances in Genetic Programming II, pp.467-488, 1996.
URL : https://hal.archives-ouvertes.fr/hal-00112301

H. Schwefel, Numerical Optimization of Computer Models, 1981.

H. Schwefel and G. Rudolf, Contemporary evolution strategies, Proc. of the 3 rd Int. Conf. on Artificial Life, pp.893-907
DOI : 10.1007/3-540-59496-5_351
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.34.417

B. Schölkopf, C. Burges, and A. Smola, Advances in Kernel Methods : Support Vector Machines, 1998.

M. Sebag and A. Ducoulombier, Extending population-based incremental learning to continuous search spaces, Proceedings of the 5 th Conference on Parallel Problems Solving from Nature, pp.418-427, 1998.
DOI : 10.1007/BFb0056884
URL : https://hal.archives-ouvertes.fr/hal-00116542

M. Sebag, M. Schoenauer, and M. Peyral, Revisiting the memory of evolution, Fundamenta Informaticae, vol.38, pp.1-39, 1998.
URL : https://hal.archives-ouvertes.fr/hal-00111603

H. Simon, Models of Bounded Rationality, 1982.

R. E. Smith and E. Smuda, Adaptatively resizing populations : algorithm, analysis and first results, Complex Systems, vol.9, pp.47-72, 1995.

G. Soremekun, Z. Gürdal, R. T. Haftka, and L. T. Watson, Composite laminate design optimization by genetic algorithm with generalized elitist selection, Computers & Structures, vol.79, issue.2, pp.131-143, 2001.
DOI : 10.1016/S0045-7949(00)00125-5

P. N. Suganthan, N. Hansen, J. J. Liang, K. Deb, Y. Chen et al., Problem definitions and evaluation criteria for the cec 2005 special session on real-parameter optimization, IIT Kanpur, 2005.

V. N. Vapnik, Statistical Learning Theory, 1998.

M. D. Vose, The Simple Genetic Algorithm, 1999.

P. A. Whigham, Inductive bias and genetic programming, 1st International Conference on Genetic Algorithms in Engineering Systems: Innovations and Applications (GALESIA), pp.461-466, 1995.
DOI : 10.1049/cp:19951092

L. D. Whitley, Fundamental Principles of Deception in Genetic Search, Foundations of Genetic Algorithms, pp.221-241
DOI : 10.1016/B978-0-08-050684-5.50017-3

L. D. Whitley, T. Starkweather, and D. Shaner, Handbook of Genetic Algorithms , chapter Traveling salesman and sequence scheduling : quality solutions using genetic edge recombination, pp.350-372, 1991.

D. H. Wolpert and W. G. Macready, No free lunch theorems for search, 1995.