A. Neumaier, Molecular Modeling of Proteins and Mathematical Prediction of Protein Structure, SIAM Review, vol.39, issue.3, pp.407-460, 1997.
DOI : 10.1137/S0036144594278060

R. Thomsen, Protein???Ligand Docking with Evolutionary Algorithms, Computational Intelligence in Bioinformatics, pp.169-195, 2008.
DOI : 10.1002/9780470199091.ch8

G. M. Morris, A. J. Olson, and D. S. Goodsell, Protein-Ligand Docking, pp.31-48, 2000.
DOI : 10.1002/9783527613168.ch3

R. Thomsen, Flexible ligand docking using evolutionary algorithms: investigating the effects of variation operators and local search hybrids, Biosystems, vol.72, issue.1-2, pp.57-73, 2003.
DOI : 10.1016/S0303-2647(03)00135-7

B. Sendhoff, M. Kreutz, and W. V. Seelen, A condition for the genotypephenotype mapping: Casualty, 7th Int. Conf. on Genetic Algorithms, pp.73-80, 1997.

F. Rothlauf, On the Locality of Representations, Proceedings of the Genetic and Evolutionary Computation Conference, pp.1608-1609, 2003.
DOI : 10.1007/3-540-45110-2_48

G. R. Raidl and J. Gottlieb, Empirical Analysis of Locality, Heritability and Heuristic Bias in Evolutionary Algorithms: A Case Study for the Multidimensional Knapsack Problem, Evolutionary Computation, vol.32, issue.4, pp.441-475, 2005.
DOI : 10.1162/106365602317301781

B. A. Julstrom, The blob code: A better string coding of spanning trees for evolutionary search, GECCO '01: Proceedings of the 2001 conference on Genetic and evolutionary computation, pp.256-261, 2001.

S. M. Soak, D. W. Corne, and B. H. Ahn, The edge-window-decoder representation for tree-based problems, IEEE Transactions on Evolutionary Computation, vol.10, issue.2, pp.124-144, 2006.
DOI : 10.1109/TEVC.2006.871250

G. M. Morris, D. S. Goodsell, R. S. Halliday, R. Huey, W. E. Hart et al., Automated docking using a Lamarckian genetic algorithm and an empirical binding free energy function, Journal of Computational Chemistry, vol.4, issue.14, pp.1639-1662, 1998.
DOI : 10.1002/(SICI)1096-987X(19981115)19:14<1639::AID-JCC10>3.0.CO;2-B

F. B. Pereira, J. Marques, T. Leitão, and J. Tavares, Analysis of Locality in Hybrid Evolutionary Cluster Optimization, 2006 IEEE International Conference on Evolutionary Computation, pp.8049-8056, 2006.
DOI : 10.1109/CEC.2006.1688590

J. Tavares, A. A. Tantar, N. Melab, and E. G. Talbi, The Influence of Mutation on Protein-Ligand Docking Optimization: A Locality Analysis, Proceedings of the 10th International Conference on Parallel Problem Solving From Nature, 2008.
DOI : 10.1007/978-3-540-87700-4_59
URL : https://hal.archives-ouvertes.fr/hal-00690373

J. S. Dixon, Flexible docking of ligands to receptor sites using genetic algorithms, Proc. of the 9th European Symposium on Structure-Activity Relationships, pp.412-413, 1993.

Y. L. Xiao and D. E. Williams, Molecular docking using genetic algorithms, Proceedings of the 1994 ACM symposium on Applied computing , SAC '94, pp.196-200, 1994.
DOI : 10.1145/326619.326721

J. C. Meza, R. S. Judson, T. R. Faulkner, and A. M. Treasurywala, A comparison of a direct search method and a genetic algorithm for conformational searching, Journal of Computational Chemistry, vol.1, issue.9, pp.1142-1151, 1996.
DOI : 10.1002/(SICI)1096-987X(19960715)17:9<1142::AID-JCC6>3.0.CO;2-S

D. K. Gehlhaar, G. Verkhivker, P. A. Rejto, D. B. Fogel, L. J. Fogel et al., Docking conformationally flexible small molecules into a protein binding site through evolutionary programming, In: Evolutionary Programming, pp.615-627, 1995.

N. Moitessier, P. Englebienne, D. Lee, J. Lawandi, and C. Corbeil, Towards the development of universal, fast and highly accurate docking/scoring methods: a long way to go, British Journal of Pharmacology, vol.666, issue.667, pp.1-20, 2007.
DOI : 10.1038/sj.bjp.0707515

K. Deb and H. Georg-beyer, Self-Adaptive Genetic Algorithms with Simulated Binary Crossover, Evolutionary Computation, vol.3, issue.2, pp.197-221, 2001.
DOI : 10.1016/0303-2647(95)01534-R

M. Lozano, F. Herrera, N. Krasnogor, and D. Molina, Real-Coded Memetic Algorithms with Crossover Hill-Climbing, Evolutionary Computation, vol.36, issue.10, pp.12-273, 2004.
DOI : 10.1109/4235.996022

O. Korb, T. Stützle, and T. Exner, An ant colony optimization approach to flexible protein???ligand docking, Swarm Intelligence, vol.22, issue.3, pp.115-134, 2007.
DOI : 10.1007/s11721-007-0006-9
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.470.5706

B. Manderick, M. De-weger, and P. Spiessens, The genetic algorithm and the structure of the fitness landscape, 4th International Conference on Genetic Algorithms, pp.143-150, 1991.

S. Wright, The roles of mutation, inbreeding, crossbreeding and selection in evolution, Proceedings of the VI International Conference on Genetics, pp.356-366, 1932.

T. Jones, Evolutionary Algorithms, Fitness Landscapes and Search, 1995.

T. Jones and S. Forrest, Fitness distance correlation as a measure of problem difficulty for genetic algorithms, Proceedings of the Sixth International Conference on Genetic Algorithms, pp.184-192, 1995.

E. D. Weinberger, Correlated and uncorrelated fitness landscapes and how to tell the difference, Biological Cybernetics, vol.1, issue.5, pp.325-336, 1990.
DOI : 10.1007/BF00202749

P. Merz and B. Freisleben, Fitness landscapes and memetic algorithm design
DOI : 10.1162/106365600568103
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.5.6968

P. Merz, Memetic Algorithms for Combinatorial Optimization Problems: Fitness Landscapes and Efective Search Strategies, 2000.

J. Tavares, Evolvability in Optimization Problems: the Role of Representations and Heuristics, Portugal, 2007.

J. Tavares, F. B. Pereira, and E. Costa, Multidimensional Knapsack Problem: A Fitness Landscape Analysis, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), vol.38, issue.3, pp.604-616, 2008.
DOI : 10.1109/TSMCB.2008.915539

F. Rothlauf, Representations for Genetic and Evolutionary Algorithms, 2002.
DOI : 10.1007/978-3-642-88094-0

J. Tavares, A. A. Tantar, N. Melab, and E. G. Talbi, The Impact of Local Search on Protein-Ligand Docking Optimization, 2008 Eighth International Conference on Hybrid Intelligent Systems, 2008.
DOI : 10.1109/HIS.2008.14
URL : https://hal.archives-ouvertes.fr/hal-00684472