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

D. V. Arnold and J. Porter, Towards an Augmented Lagrangian Constraint Handling Approach for the (1+1)-ES, Proceedings of the 2015 on Genetic and Evolutionary Computation Conference, GECCO '15, pp.249-256, 2015.
DOI : 10.1145/1068009.1068114

A. Atamna, A. Auger, and N. Hansen, Analysis of Linear Convergence of a (1 + 1)-ES with Augmented Lagrangian Constraint Handling, Proceedings of the 2016 on Genetic and Evolutionary Computation Conference, GECCO '16, pp.213-220, 2016.
DOI : 10.1007/978-1-4471-3267-7
URL : https://hal.archives-ouvertes.fr/hal-01318807

A. Atamna, A. Auger, and N. Hansen, Augmented Lagrangian Constraint Handling for CMA-ES ??? Case of a Single Linear Constraint, Parallel Problem Solving from Nature, pp.181-191, 2016.
DOI : 10.1023/B:NACO.0000023416.59689.4e
URL : https://hal.archives-ouvertes.fr/hal-01390386

A. Atamna, A. Auger, and N. Hansen, Linearly Convergent Evolution Strategies via Augmented Lagrangian Constraint Handling, Proceedings of the 14th ACM/SIGEVO Conference on Foundations of Genetic Algorithms, FOGA '17, pp.149-161, 2017.
DOI : 10.1109/4235.850652
URL : https://hal.archives-ouvertes.fr/hal-01455379

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 and N. Hansen, Linear Convergence on Positively Homogeneous Functions of a Comparison Based Step-Size Adaptive Randomized Search: the (1 + 1) ES with Generalized One-Fifth Success Rule, 2013.
URL : https://hal.archives-ouvertes.fr/hal-00877161

A. Auger and N. Hansen, Linear Convergence of Comparison-based Step-size Adaptive Randomized Search via Stability of Markov Chains, SIAM Journal on Optimization, vol.26, issue.3, pp.1589-1624, 2016.
DOI : 10.1137/140984038
URL : https://hal.archives-ouvertes.fr/hal-00877160

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.1-3269, 2003.
DOI : 10.1016/S0304-3975(03)00284-6

E. G. Birgin, C. A. Floudas, and J. M. Martínez, Global minimization using an Augmented Lagrangian method with variable lower-level constraints, Mathematical Programming, pp.139-162, 2010.
DOI : 10.1007/978-1-4419-9182-9

A. Chotard and A. Auger, Verifiable Conditions for Irreducibility, Aperiodicity and T-chain Property of a General Markov Chain Accepted for publication in Bernoulli, 2015.

A. R. Conn, N. I. Gould, and P. L. Toint, A Globally Convergent Augmented Lagrangian Algorithm for Optimization with General Constraints and Simple Bounds, SIAM Journal on Numerical Analysis, vol.28, issue.2, pp.545-572, 1991.
DOI : 10.1137/0728030

K. Deb and S. Srivastava, A genetic algorithm based augmented Lagrangian method for constrained optimization, Computational Optimization and Applications, vol.52, issue.1, pp.869-902, 2012.
DOI : 10.1007/s10898-011-9688-z

N. Hansen, The CMA Evolution Strategy: A Tutorial, 2016.
URL : https://hal.archives-ouvertes.fr/hal-01297037

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

M. R. Hestenes, Multiplier and gradient methods, Journal of Optimization Theory and Applications, vol.4, issue.5, pp.303-320, 1969.
DOI : 10.1007/BF00927673

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

S. P. Meyn and R. L. Tweedie, Markov Chains and Stochastic Stability, 1993.

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

M. J. Powell, A Method for Nonlinear Constraints in Minimization Problems, pp.283-298, 1969.

M. Tahk and B. Sun, Coevolutionary augmented Lagrangian methods for constrained optimization, IEEE Transactions on Evolutionary Computation, vol.4, issue.2, pp.114-124, 2000.
DOI : 10.1109/4235.850652