Nikolaus Hansen

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Anne AugerInria, CMAP Ecole Polytechnique, IP ParisVerified email at inria.fr
Dimo BrockhoffInria, Ecole Polytechnique, Institut Polytechnique de ParisVerified email at inria.fr
Petros KoumoutsakosHarvard UniversityVerified email at seas.harvard.edu
Steffen FinckVorarlberg University of Applied Sciences, Research Center Business InformaticsVerified email at fhv.at
Tea TušarSenior Research Associate, Jožef Stefan InstituteVerified email at ijs.si
Christian IgelDepartment of Computer Science, University of CopenhagenVerified email at diku.dk
Stefan KernStadtwerke MünchenVerified email at swm.de
Youhei AkimotoUniversity of TsukubaVerified email at cs.tsukuba.ac.jp
Kalyanmoy DebUniversity Distinguished Professor, Electrical and Computer Engineering, Michigan State UniversityVerified email at egr.msu.edu
Marc SchoenauerSenior Researcher Emeritus, INRIAVerified email at inria.fr
Olaf MersmannTH KölnVerified email at p-value.net
Dirk V. ArnoldProfessor, Faculty of Computer Science, Dalhousie UniversityVerified email at dal.ca
Petr PošíkResearcher, Czech Technical University in PragueVerified email at fel.cvut.cz
R. Prof. P. N. Suganthan, FIEEE'2015,...KINDI Computing Research, Qatar University (Hon Doc: U of Maribor; BA/MA: Cambridge U, UKVerified email at qu.edu.qa
J Liang (梁静)Zhengzhou UniversityVerified email at zzu.edu.cn
Ying-ping ChenNational Yang Ming Chiao Tung UniversityVerified email at cs.nycu.edu.tw
Asma AtamnaRuhr-Universität BochumVerified email at ini.rub.de
Lino GuzzellaETH ZurichVerified email at ethz.ch
Tobias WagnerInstitute of Machining Technology (ISF), TU DortmundVerified email at isf.de
Cheikh TourePhDVerified email at polytechnique.edu

Nikolaus Hansen

Inria & Ecole Polytechnique & Institut Polytechnique de Paris, France

Verified email at Inria.fr - Homepage

Computational Intelligence Evolutionary Algorithms Evolutionary Computation Numerical Optimization Optimization


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Completely derandomized self-adaptation in evolution strategies N Hansen, A Ostermeier Evolutionary computation 9 (2), 159-195, 2001	5134	2001
Problem definitions and evaluation criteria for the CEC 2005 special session on real-parameter optimization PN Suganthan, N Hansen, JJ Liang, K Deb, YP Chen, A Auger, S Tiwari KanGAL report 2005005 (2005), 2005, 2005	2892	2005
Reducing the time complexity of the derandomized evolution strategy with covariance matrix adaptation (CMA-ES) N Hansen, SD Müller, P Koumoutsakos Evolutionary computation 11 (1), 1-18, 2003	2890	2003
The CMA evolution strategy: a comparing review N Hansen Towards a new evolutionary computation: Advances in the estimation of …, 2006	2650	2006
The CMA evolution strategy: A tutorial N Hansen Inria, 2005	1874*	2005
Adapting arbitrary normal mutation distributions in evolution strategies: The covariance matrix adaptation N Hansen, A Ostermeier Proceedings of IEEE international conference on evolutionary computation …, 1996	1684	1996
USPEX—Evolutionary crystal structure prediction CW Glass, AR Oganov, N Hansen Computer physics communications 175 (11-12), 713-720, 2006	1317	2006
A restart CMA evolution strategy with increasing population size A Auger, N Hansen 2005 IEEE congress on evolutionary computation 2, 1769-1776, 2005	1247	2005
Evaluating the CMA evolution strategy on multimodal test functions N Hansen, S Kern International conference on parallel problem solving from nature, 282-291, 2004	1072	2004
Covariance matrix adaptation for multi-objective optimization C Igel, N Hansen, S Roth Evolutionary computation 15 (1), 1-28, 2007	983	2007
Real-parameter black-box optimization benchmarking 2009: Noiseless functions definitions N Hansen, S Finck, R Ros, A Auger INRIA, 2009	673	2009
Real-parameter black-box optimization benchmarking 2010: Experimental setup N Hansen, A Auger, S Finck, R Ros INRIA, 2010	563	2010
Comparing results of 31 algorithms from the black-box optimization benchmarking BBOB-2009 N Hansen, A Auger, R Ros, S Finck, P Pošík Proceedings of the 12th annual conference companion on Genetic and …, 2010	547	2010
COCO: A platform for comparing continuous optimizers in a black-box setting N Hansen, A Auger, R Ros, O Mersmann, T Tušar, D Brockhoff Optimization Methods and Software 36 (1), 114-144, 2021	529	2021
Benchmarking a BI-population CMA-ES on the BBOB-2009 function testbed N Hansen Proceedings of the 11th annual conference companion on genetic and …, 2009	370	2009
A method for handling uncertainty in evolutionary optimization with an application to feedback control of combustion N Hansen, ASP Niederberger, L Guzzella, P Koumoutsakos IEEE Transactions on Evolutionary Computation 13 (1), 180-197, 2008	369	2008
Performance evaluation of an advanced local search evolutionary algorithm A Auger, N Hansen 2005 IEEE congress on evolutionary computation 2, 1777-1784, 2005	356	2005
Learning probability distributions in continuous evolutionary algorithms–a comparative review S Kern, SD Müller, N Hansen, D Büche, J Ocenasek, P Koumoutsakos Natural Computing 3, 77-112, 2004	336	2004
A simple modification in CMA-ES achieving linear time and space complexity R Ros, N Hansen International conference on parallel problem solving from nature, 296-305, 2008	326	2008
Information-geometric optimization algorithms: A unifying picture via invariance principles Y Ollivier, L Arnold, A Auger, N Hansen Journal of Machine Learning Research 18 (18), 1-65, 2017	317	2017

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