Livre blanc sur les énergies. Ministère de l'économie, des nances et de l'industrie, 2003. ,
Modélisation markal pour la planication énergétique long terme dans le contexte français Available: http://pastel.archives-ouvertes, p.2752, 2006. ,
How deadly is your kilowatt? we rank the killer en- ergy sources, http://www.forbes.com/sites/jamesconca, pp.2012-2010, 2012. ,
Assessing "dangerous climate change": required reduction of carbon emissions to protect young people, future generations and nature, PloS one, vol.8, issue.12, 2013. ,
Power Generation, Operation and Control, 2013. ,
A genetic algorithm solution to the unit commitment problem, Power Systems, IEEE Transactions on, vol.11, issue.1, p.8392, 1996. ,
Unit commitment-a bibliographical survey, Power Systems, IEEE Transactions on, vol.19, issue.2, p.11961205, 2004. ,
Unit commitment literature synopsis, Power Systems, IEEE Transactions on, vol.9, issue.1, p.128135, 1994. ,
Solution of the mixed integer large scale unit commitment problem by means of a continuous Stochastic linear programming model, Energy Systems, vol.11, issue.3, p.269284, 2014. ,
DOI : 10.1007/s12667-013-0107-z
Power generation, operation, and control Available: http://books.google.fr/books?id=dwRtAAAAIAAJ [17] RTE, Developpement durable, 1984. ,
com/fr/developpement-durable/les-enjeux-1/ les-metiers-de-rte-et-les-enjeux-de-developpement-durable/ les-metiers-les-enjeux, pp.2010-2019, 2011. ,
Les réseaux de transport et distribution d'électricité, pp.2010-2019, 2013. ,
A review of unit commitment, 2013. ,
Renewable energy forecasts ought to be probabilistic, 2013, wIP- FOR seminar ,
Conduite d'un système de production-transport, Techniques de l'ingénieur Réseaux électriques de transport et de répartition, 2000. ,
Adaptive robust optimization for the security constrained unit commitment problem, Power Systems, IEEE Transactions on, vol.28, issue.1, p.5263, 2013. ,
Approximate Dynamic Programming: Solving the Curses of Dimensionality (Wiley Series in Probability and Statistics), 2007. ,
Dynamic Programming and Optimal Control, vols I and II ,
Reinforcement Learning: An Introduction, IEEE Transactions on Neural Networks, vol.9, issue.5, 1998. ,
DOI : 10.1109/TNN.1998.712192
Markov Decision Processes: Discrete Stochastic Dynamic Programming Available: http://www.amazon.ca, pp.9-20, 1994. ,
DOI : 10.1002/9780470316887
Optimisation des actifs hydrauliques d'edf : besoins métiers, méthodes actuelles et perspectives, 2012, pGMO. [30] A. Couetoux, Monte carlo tree search for continuous and stochastic sequential decision making problems, 2013. ,
Dynamic Programming and Markov Processes, 1960. ,
Contracting Markov Decision Processes Amsterdam : Mathematisch Centrum, 1976. ,
Modied policy iteration algorithms for discounted Markov decision problems, Management Science, vol.24, issue.11, p.11271137, 1978. ,
Scenario tree reduction for multistage stochastic programs, Computational Management Science, vol.18, issue.2, pp.117133117-133, 2009. ,
DOI : 10.1007/s10287-008-0087-y
Dynamic Programming and Suboptimal Control: A Survey from ADP to MPC*, European Journal of Control, vol.11, issue.4-5, pp.4-5, 2005. ,
DOI : 10.3166/ejc.11.310-334
Multi-stage stochastic optimization applied to energy planning, Mathematical Programming, vol.4, issue.1-3, p.359375, 1991. ,
DOI : 10.1007/BF01582895
Analysis of stochastic dual dynamic programming method, European Journal of Operational Research, vol.209, issue.1, p.6372, 2011. ,
DOI : 10.1016/j.ejor.2010.08.007
Optimal control of Markov decision processes with incomplete state estimation, Journal of Mathematical Analysis and Applications, vol.10, p.174205, 1965. ,
Neuro-dynamic Programming, Athena Scientic, 1996. ,
Hoeding and bernstein races for selecting policies in evolutionary direct policy search, ICML '09: Proceedings of the 26th Annual International Conference on Machine Learning, p.401408, 2009. ,
Convergent Cutting-Plane and Partial-Sampling Algorithm for Multistage Stochastic Linear Programs with Recourse, Journal of Optimization Theory and Applications, vol.75, issue.3, p.497524, 1999. ,
DOI : 10.1023/A:1022641805263
The abridged nested decomposition method for multistage stochastic linear programs with relatively complete recourse, Algorithmic Operations Research, vol.1, issue.1, 2006. ,
On the Convergence of Sampling-Based Decomposition Algorithms for Multistage Stochastic Programs, Journal of Optimization Theory and Applications, vol.10, issue.2, p.349366, 2005. ,
DOI : 10.1007/s10957-004-1842-z
On the convergence of stochastic dual dynamic programming and related methods, Operations Research Letters, vol.36, issue.4, pp.450-455, 2008. ,
DOI : 10.1016/j.orl.2008.01.013
Stochastic approximation of minima with improved asymptotic speed The Theory of Evolutions Strategies Teytaud, log-log convergence for noisy optimization, Proceedings of EA 2013, p.p. accepted, 1967. ,
Reducing the Time Complexity of the Derandomized Evolution Strategy with Covariance Matrix Adaptation (CMA-ES), Evolutionary Computation, vol.11, issue.1, p.118, 2003. ,
DOI : 10.1162/106365601750190398
Recent progress in unconstrained nonlinear optimization without derivatives, Mathematical Programming, vol.12, issue.1, 1997. ,
DOI : 10.1007/BF02614326
Towards a Complexity Theory of Randomized Search Heuristics: Ranking-Based Black-Box Complexity, Lecture Notes in Computer Science, vol.23 ,
DOI : 10.1017/CBO9780511814075
Numerical Optimization of Computer Models, 1981. ,
Mutate large, but inherit small ! On the analysis of mutations in (1, ?)-ES with noisy tness data, p.109118, 1998. ,
Genetic algorithms in noisy environments, in machine learning: Special issue on genetic algorithms, 1988. ,
Local performance of the (1 + 1)-ES in a noisy environment, IEEE Transactions on Evolutionary Computation, vol.6, issue.1, p.3041, 2002. ,
DOI : 10.1109/4235.985690
Evolution strategies with cumulative step length adaptation on the noisy parabolic ridge, Natural Computing, vol.2, issue.2, 2006. ,
DOI : 10.1007/s11047-006-9025-5
Evolution strategies on noisy functions: How to improve convergence properties, in Parallel Problem Solving From Nature ,
Genetic algorithms in noisy environments, Machine Learning, p.101120, 1988. ,
DOI : 10.1007/BF00113893
On multiplicative noise models for stochastic search, in Parallel Problem Solving From Nature, dortmund Allemagne, 2008. ,
On the adaptation of noise level for stochastic optimization, 2007 IEEE Congress on Evolutionary Computation, 2007. ,
DOI : 10.1109/CEC.2007.4424857
URL : https://hal.archives-ouvertes.fr/inria-00173224
Clop: Condent local optimization for noisy black-box parameter tuning, in ACG, ser, Lecture Notes in Computer Science, H. J. van den, vol.7168, p.146157, 2011. ,
Handling expensive optimization with large noise, Proceedings of the 11th workshop proceedings on Foundations of genetic algorithms, FOGA '11, p.6168, 2011. ,
DOI : 10.1145/1967654.1967660
URL : https://hal.archives-ouvertes.fr/hal-00517157
Bandit-Based Estimation of Distribution Algorithms for Noisy Optimization: Rigorous Runtime Analysis, Proceedings of Lion4 (accepted), 2009. ,
DOI : 10.1007/978-3-642-13800-3_8
URL : https://hal.archives-ouvertes.fr/inria-00437140
Uncertainty handling CMA-ES for reinforcement learning, Proceedings of the 11th Annual conference on Genetic and evolutionary computation, GECCO '09, p.12111218, 2009. ,
DOI : 10.1145/1569901.1570064
A probabilistic Theory of Pattern Recognition, 1997. ,
DOI : 10.1007/978-1-4612-0711-5
Handling expensive optimization with large noise, Proceedings of the 11th workshop proceedings on Foundations of genetic algorithms, FOGA '11, p.6168, 2011. ,
DOI : 10.1145/1967654.1967660
URL : https://hal.archives-ouvertes.fr/hal-00517157
Ecient global optimization of expensive black-box functions, J. of Global Optimization, vol.13, issue.4, p.455492, 1998. ,
An informational approach to the global optimization of expensive-to-evaluate functions, Journal of Global Optimization, vol.10, issue.5, p.26, 2008. ,
DOI : 10.1007/s10898-008-9354-2
URL : https://hal.archives-ouvertes.fr/hal-00354262
Considérations à l'appui de la découverte de laplace, Comptes Rendus de l, Académie des Sciences, vol.37, p.309324, 1853. ,
Sur les valeurs limites des integrales, Math Pure Appl, vol.19, pp.157160-1874 ,
On certain applications of algebraic continued fractions, 2002. ,
General Lower Bounds for Evolutionary Algorithms, 10 th International Conference on Parallel Problem Solving from Nature, 2006. ,
DOI : 10.1007/11844297_3
URL : https://hal.archives-ouvertes.fr/inria-00112820
Lower Bounds for Comparison Based Evolution Strategies Using VC-dimension and Sign Patterns, Algorithmica, vol.XVI, issue.2, p.387408, 2011. ,
DOI : 10.1007/s00453-010-9391-3
URL : https://hal.archives-ouvertes.fr/inria-00452791
Convergence results for (1,?)-SA-ES using the theory of ?irreducible Markov chains, Theoretical Computer Science, vol.334, issue.1-3, p.3569, 2005. ,
Local and global order 3/2 convergence of a surrogate evolutionnary algorithm, Gecco, p.8, 2005. ,
Eciency and mutation strength adaptation of the (mu/mui,lambda)-es in a noisy environment, Parallel Problem Solving from Nature, p.3948, 1917. ,
The Theory of Evolution Strategies, ser. Natural Computing Se- ries ,
Lower Rate of Convergence for Locating a Maximum of a Function, The Annals of Statistics, vol.16, issue.3, p.13301334, 1988. ,
DOI : 10.1214/aos/1176350965
Stochastic estimation of the maximum of a regression function, Annals of Mathematical Statistics, vol.23, issue.3, p.462466, 1952. ,
Global optimization based on noisy evaluations: An empirical study of two statistical approaches, Journal of Physics: Conference Series, vol.135, p.17, 2008. ,
DOI : 10.1088/1742-6596/135/1/012100
URL : https://hal.archives-ouvertes.fr/hal-00278188
Randomization of Number Theoretic Methods for Multiple Integration, SIAM Journal on Numerical Analysis, vol.13, issue.6, p.904914, 1976. ,
DOI : 10.1137/0713071
On the scrambled halton sequence, Monte-Carlo Methods Appl, p.435442, 2004. ,
Randomized Halton sequences, Mathematical and Computer Modelling, vol.32, issue.7-8, p.887899, 2000. ,
DOI : 10.1016/S0895-7177(00)00178-3
Generating quasi-random paths for stochastic processes, p.765788, 1998. ,
Scenario reduction in stochastic programming: An approach using probability metrics, ser. Stochastic Programming E-Print Series ,
On the stratication of skewed populations Available: http://www.amstat.org/sections/srms, Survey Methodology, vol.14, issue.1, p.3343, 1988. ,
A note on optimum stratication of populations for estimating the population means Optimal stratication using random search method in agricultural surveys, Australian Journal of Statistics Statistics in Transition, vol.5, issue.6 5, pp.2033-797806, 1963. ,
The empirical behavior of sampling methods for stochastic programming, Annals of Operations Research, vol.29, issue.1, p.215241, 2006. ,
DOI : 10.1007/s10479-006-6169-8
Monte-Carlo Simulation Balancing in Practice, Computers and Games, p.8192, 2010. ,
DOI : 10.1007/978-3-642-17928-0_8
Continuous functions minimization by dynamic random search technique, Applied Mathematical Modelling, vol.31, issue.10, p.21892198, 2007. ,
DOI : 10.1016/j.apm.2006.08.015
Random search algorithms, Wiley Encyclopedia of Operations Research and Management Science, 2009. ,
Dierential evolutiona simple and ecient heuristic for global optimization over continuous spaces, Journal of global optimization, vol.11, issue.4, p.341359, 1997. ,
Paired comparison-based interactive dierential evolution, Nature & Biologically Inspired Computing NaBIC, p.475480, 2009. ,
Direct policy search using paired statistical tests, Proceedings of the 18th International Conference on Machine Learning, p.545552, 2001. ,
Policy search using paired comparisons, Journal of Machine Learning Research, p.921950, 2002. ,
Simulation-Based Optimization with Stochastic Approximation Using Common Random Numbers, Management Science, vol.45, issue.11, p.15701578, 1999. ,
DOI : 10.1287/mnsc.45.11.1570
Improving the performance of Stochastic Dual Dynamic Programming, Journal of Computational and Applied Mathematics, vol.290, p.2012 ,
DOI : 10.1016/j.cam.2015.04.048
Risk neutral and risk averse Stochastic Dual Dynamic Programming method, European Journal of Operational Research, vol.224, issue.2, p.375391, 2012. ,
DOI : 10.1016/j.ejor.2012.08.022
The ???Pegasus??? method for computing the root of an equation, BIT, vol.11, issue.4, p.503508, 1972. ,
DOI : 10.1007/BF01932959
CUTEr and SifDec, ACM Transactions on Mathematical Software, vol.29, issue.4, p.373394, 2003. ,
DOI : 10.1145/962437.962439
A survey of evolution strategies, 1991. ,
Conditionning, halting criteria and choosing lambda, in EA07, 2007. ,
On the optimization of unimodal functions with the (1+1) evolutionary algorithm, in Parallel Problem Solving from Nature -PPSN V, ser, Lecture Notes in Computer Science ,
On the uniform convergence of relative frequencies of events to their probabilities, Theory of probability and its applications, pp.264-280, 1971. ,
Stratégies d'évolution dérandomisées, Tech. Rep, 2007. ,
Completely derandomized self-adaptation in evolution strategies Step-size adaptation based on non-local use of selection information, Parallel Problem Solving from Nature -PPSN III, pp.159195-189198, 1994. ,
Covariance Matrix Adaptation Revisited ??? The CMSA Evolution Strategy ???, p.123132, 2008. ,
DOI : 10.1007/978-3-540-87700-4_13