The Theory of Evolution Strategies, ser. Natural Computing Series, 2001. ,
Adapting arbitrary normal mutation distributions in evolution strategies: the covariance matrix adaptation, Proceedings of IEEE International Conference on Evolutionary Computation, pp.312-317, 1996. ,
DOI : 10.1109/ICEC.1996.542381
Covariance Matrix Adaptation Revisited ??? The CMSA Evolution Strategy ???, Proceedings of PPSN, pp.123-132, 2008. ,
DOI : 10.1007/978-3-540-87700-4_13
Low-discrepancy and low-dispersion sequences, Journal of Number Theory, vol.30, issue.1, 1988. ,
DOI : 10.1016/0022-314X(88)90025-X
URL : http://doi.org/10.1016/0022-314x(88)90025-x
Incremental low-discrepancy lattice methods for motion planning, 2003 IEEE International Conference on Robotics and Automation (Cat. No.03CH37422), pp.2920-2927, 2003. ,
DOI : 10.1109/ROBOT.2003.1242039
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.115.7406
Genetic algorithms using low-discrepancy sequences, Proceedings of the 2005 conference on Genetic and evolutionary computation , GECCO '05, pp.1341-1346, 2005. ,
DOI : 10.1145/1068009.1068225
A hybrid meta-heuristic for global optimisation using low-discrepancy sequences of points Computers and Operations Research, -special issue on hybrid metaheuristics ,
DCMA, yet another derandomization in covariancematrix-adaptation, pp.955-922, 2007. ,
When Does Quasi-random Work?, PPSN, ser. Lecture Notes in Computer Science, pp.325-336, 2008. ,
DOI : 10.1007/978-3-540-87700-4_33
URL : https://hal.archives-ouvertes.fr/inria-00287863
Completely Derandomized Self-Adaptation in Evolution Strategies, Evolutionary Computation, vol.9, issue.2, 2003. ,
DOI : 10.1016/0004-3702(95)00124-7
Computational Investigations of Low-Discrepancy Point Sets II, Applications of Number Theory to Numerical Analysis (Proceedings of the Symposium), p.319343, 1972. ,
DOI : 10.1007/978-1-4612-2552-2_23
On the Scrambled Halton Sequence, Monte Carlo Methods and Applications, vol.10, issue.3-4, pp.435-442, 2004. ,
DOI : 10.1515/mcma.2004.10.3-4.435
Randomized Halton sequences, Mathematical and Computer Modelling, vol.32, issue.7-8, pp.887-899, 2000. ,
DOI : 10.1016/S0895-7177(00)00178-3
URL : http://doi.org/10.1016/s0895-7177(00)00178-3
A new permutation choice in Halton sequences, p.427435, 1997. ,
DOI : 10.1007/978-1-4612-1690-2_30
On the Systematic Search in a Hypercube, SIAM Journal on Numerical Analysis, vol.16, issue.5, pp.790-793, 1979. ,
DOI : 10.1137/0716058
Multidimensional Variation for Quasi-Monte Carlo, 2004. ,
DOI : 10.1142/9789812567765_0004
Good permutations for deterministic scrambled halton sequences in terms of l2-discrepancy, Computational and Applied Mathematics, vol.189, issue.12, p.341361, 2006. ,
On the huge benefit of quasi-random mutations for multimodal optimization with application to grid-based tuning of neurocontrollers, ESANN, 2009. ,
URL : https://hal.archives-ouvertes.fr/inria-00380125
On the ultimate convergence rates for isotropic algorithms and the best choices among various forms of isotropy, Parallel Problem Solving from Nature-PPSN IX, 2006. ,
URL : https://hal.archives-ouvertes.fr/inria-00112816