B. Alatas, E. Akin, and A. Karci, MODENAR: Multi-objective differential evolution algorithm for mining numeric association rules, Applied Soft Computing, vol.8, issue.1, pp.646-656, 2008.
DOI : 10.1016/j.asoc.2007.05.003

P. Auer, N. Cesa-bianchi, and P. Fischer, Finite-time analysis of the multiarmed bandit problem, Machine Learning, vol.47, issue.2/3, pp.235-256, 2002.
DOI : 10.1023/A:1013689704352

A. Auger and N. Hansen, A Restart CMA Evolution Strategy With Increasing Population Size, 2005 IEEE Congress on Evolutionary Computation, pp.1769-1776, 2005.
DOI : 10.1109/CEC.2005.1554902

M. Birattari, T. Stützle, L. Paquete, and K. Varrentrapp, A racing algorithm for configuring metaheuristics, Proc. GECCO, pp.11-18, 2002.

A. P. Bradley, The use of the area under the ROC curve in the evaluation of machine learning algorithms, Pattern Recognition, vol.30, issue.7, pp.1145-1159, 1997.
DOI : 10.1016/S0031-3203(96)00142-2

U. Chakraborty, Advances in Differential Evolution, 2008.
DOI : 10.1007/978-3-540-68830-3

L. Costa, A. Fialho, M. Schoenauer, and M. Sebag, Adaptive operator selection with dynamic multi-armed bandits, Proc. GECCO, pp.913-920, 2008.
URL : https://hal.archives-ouvertes.fr/inria-00278542

S. Das, A. Abraham, and A. Konar, Automatic Clustering Using an Improved Differential Evolution Algorithm, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans, vol.38, issue.1, pp.218-237, 2008.
DOI : 10.1109/TSMCA.2007.909595

V. Feoktistov, Differential Evolution: In Search of Solutions, 2006.

A. Fialho, L. Da-costa, M. Schoenauer, and M. Sebag, Extreme Value Based Adaptive Operator Selection, Proc. PPSN X, pp.175-184, 2008.
DOI : 10.1007/978-3-540-87700-4_18

URL : https://hal.archives-ouvertes.fr/inria-00287355

A. Fialho, L. Da-costa, M. Schoenauer, and M. Sebag, Dynamic multiarmed bandits and extreme value-based rewards for adaptive operator selection in evolutionary algorithms, Proc. LION 3, pp.176-190, 2009.
URL : https://hal.archives-ouvertes.fr/inria-00377401

A. Fialho, M. Schoenauer, and M. Sebag, Analysis of adaptive operator selection techniques on the royal road and long k-path problems, Proceedings of the 11th Annual conference on Genetic and evolutionary computation, GECCO '09, pp.779-786, 2009.
DOI : 10.1145/1569901.1570009

URL : https://hal.archives-ouvertes.fr/inria-00377449

A. Fialho, M. Schoenauer, and M. Sebag, Toward comparison-based adaptive operator selection, Proceedings of the 12th annual conference on Genetic and evolutionary computation, GECCO '10, 2010.
DOI : 10.1145/1830483.1830619

URL : https://hal.archives-ouvertes.fr/inria-00471264

S. Finck, N. Hansen, R. Ros, and A. Auger, Real-parameter black-box optimization benchmarking 2009: Presentation of the noiseless functions, 2009.

D. E. Goldberg, Probability matching, the magnitude of reinforcement, and classifier system bidding, Machine Learning, vol.2, issue.4, pp.407-425, 1990.
DOI : 10.1007/BF00116878

W. Gong, A. Fialho, and Z. Cai, Adaptive strategy selection in differential evolution, Proceedings of the 12th annual conference on Genetic and evolutionary computation, GECCO '10, 2010.
DOI : 10.1145/1830483.1830559

URL : https://hal.archives-ouvertes.fr/inria-00471268

N. Hansen, Benchmarking a BI-population CMA-ES on the BBOB-2009 function testbed, Proceedings of the 11th annual conference companion on Genetic and evolutionary computation conference, GECCO '09, pp.2389-2396, 2009.
DOI : 10.1145/1570256.1570333

URL : https://hal.archives-ouvertes.fr/inria-00382093

N. Hansen, A. Auger, S. Finck, and R. Ros, Real-parameter black-box optimization benchmarking 2010: Experimental setup, 2010.
URL : https://hal.archives-ouvertes.fr/inria-00462481

N. Hansen, S. Finck, R. Ros, and A. Auger, Real-parameter black-box optimization benchmarking 2009: Noiseless functions definitions, 2009.
URL : https://hal.archives-ouvertes.fr/inria-00362633

A. W. Iorio and X. Li, Improving the Performance and Scalability of Differential Evolution, Proc. SEAL, pp.131-140, 2008.
DOI : 10.1007/BFb0056872

J. Maturana, F. Lardeux, and F. Saubion, Autonomous operator management for evolutionary algorithms, Journal of Heuristics, vol.32, issue.8, 2010.
DOI : 10.1007/s10732-010-9125-3

E. Page, CONTINUOUS INSPECTION SCHEMES, Biometrika, vol.41, issue.1-2, pp.100-115, 1954.
DOI : 10.1093/biomet/41.1-2.100

K. Price, Differential evolution vs. the functions of the second ICEO, Proc. IEEE Congress on Evol. Comp, pp.153-157, 1997.

K. Price, R. Storn, and J. Lampinen, Differential Evolution, 2005.
DOI : 10.1007/978-3-642-30504-7_8

A. K. Qin, V. L. Huang, and P. N. Suganthan, Differential Evolution Algorithm With Strategy Adaptation for Global Numerical Optimization, IEEE Transactions on Evolutionary Computation, vol.13, issue.2, pp.398-417, 2009.
DOI : 10.1109/TEVC.2008.927706

R. Storn and K. Price, Differential evolution -A simple and efficient heuristic for global optimization over continuous spaces, J. of Global Optim, vol.11, issue.4, 1997.

D. Thierens, An adaptive pursuit strategy for allocating operator probabilities, Proceedings of the 2005 conference on Genetic and evolutionary computation , GECCO '05, pp.1539-1546, 2005.
DOI : 10.1145/1068009.1068251

D. Thierens, Adaptive Strategies for Operator Allocation, Parameter Setting in Evolutionary Algorithms, pp.77-90
DOI : 10.1007/978-3-540-69432-8_4