A. Auger, Convergence Results for the (1, ?)-SA-ES Using the Theory of ?Irreducible Markov Chains, Theoretical Computer Science, vol.334, issue.1-3, pp.35-69, 2005.

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 StepSize Adaptive Randomized Search via Stability of Markov Chains, SIAM Journal on Optimization, vol.26, issue.3, pp.1589-1624, 2016.
URL : https://hal.archives-ouvertes.fr/hal-00877160

A. Bienvenüe and O. François, Global Convergence of Evolution Strategies in Spherical Problems: Some Simple Proofs and Difficulties, Theoretical Computer Science, vol.306, issue.1-3, pp.269-289, 2003.

E. G. Birgin, C. A. Floudas, and J. M. Martínez, Global Minimization Using an Augmented Lagrangian Method with Variable Lower-Level Constraints, Mathematical Programming, vol.125, issue.1, pp.139-162, 2010.

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.

K. Deb and S. Srivastava, A Genetic Algorithm Based Augmented Lagrangian Method for Constrained Optimization, Computational Optimization and Applications, vol.53, issue.3, pp.869-902, 2012.

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.

M. R. Hestenes, Multiplier and Gradient Methods, Journal of Optimization Theory and Applications, vol.4, issue.5, pp.303-320, 1969.

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.

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

J. Nocedal and S. J. Wright, Numerical Optimization, 2006.

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, IEE Transactions on Evolutionary Computation, vol.4, issue.2, pp.114-124, 2000.

, The constraints being active at x opt , h(x opt , ? opt , ?) = f (x opt )

, = ? 2 h(x opt + x, ? opt + ?, ?) + (1 ? ? 2 )f (x opt ) ? f (x opt ) = ?

, = ? 2 Dh xopt,?opt,? (x opt + x, ? opt + ?)