This list is currently outdated but may still contain links which are not available otherwise. For an up-to-date list of publications (since 2008)
see my
publications at the HAL open archive.
Many publishers tend to introduce various small (but not necessarily irrelevant) errors into manuscripts, before they publish them (sic!). (For example, they love to replace \frac{a+b}{2} with a+b/2). The risk is high for journal publications, lower for book chapters, and generally low for conference publications. In any case, please drop an email to , if you find an error.
Journals
Toure, C., A. Gissler, A. Auger, N. Hansen (2021). Scaling-invariant Functions versus Positively Homogeneous Functions. Journal of Optimization Theory and Applications [article online, abstract & pdf on HAL].
Konstantinos Varelas, K., O. Ait El-Hara, D. Brockhoff, N. Hansen, D. Manh Nguyen, T. Tušar, A. Auger (2020).
Benchmarking large-scale continuous optimizers: The bbob-largescale testbed, a COCO software guide and beyond.
Applied Soft Computing, Vol 97, Part A (DOI:10.1016/j.asoc.2020.106737,
abstract and pdf).
Akimoto, Y., A. Auger, and N. Hansen (2020).
Quality Gain Analysis of the Weighted Recombination Evolution Strategy on General Convex Quadratic Functions.
Theoretical Computer Science, 832, pp. 42-67, Elsevier
(abstract, paper).
Atamna, A., A. Auger, and N. Hansen (2018).
On Invariance and Linear Convergence of Evolution Strategies with Augmented Lagrangian Constraint Handling.
Theoretical Computer Science, Elsevier
(abstract&paper).
Akimoto, Y., A. Auger, and N. Hansen (2017).
Quality Gain Analysis of the Weighted Recombination Evolution Strategy on General Convex Quadratic Functions.
Proceedings of the 14th ACM/SIGEVO Conference on Foundations of Genetic Algorithms FOGA '17, pp.111-126,
(abstract&paper).
Ollivier, Y., L. Arnold, A. Auger and N. Hansen (2017). Information-Geometric Optimization Algorithms: A Unifying Picture via Invariance Principles. Journal of Machine Learning Research 18(18), pp. 1-65 (abstract and pdf).
Auger, A., and N. Hansen (2016). Linear Convergence of Comparison-based Step-size Adaptive Randomized Search via
Stability of Markov Chains,
SIAM Journal on Optimization, 26(3), pp. 1589-1624 (abstract and preprint).
Chotard, A., A. Auger and N. Hansen (2015). Markov Chain Analysis of Cumulative Step-size Adaptation on a Linear Constraint Problem. Evolutionary Computation, 23(4), pp. 611-640 (abstract & pdf & bibtex).
Éltetö, T., N. Hansen, C. Germain-Renaud and P. Bondon (2012). Scalable structural break detection.
Applied Soft Computing, 12(11), pp. 3408-3420 (abstract & pdf & bibtex, DOI).
Hansen, N., R. Ros, N. Mauny, M. Schoenauer and A. Auger (2011). Impacts of Invariance in Search: When CMA-ES and PSO Face Ill-Conditioned and Non-Separable Problems. Applied Soft Computing 11, 5755-5769 (abstract & pdf & bibtex, DOI, or mail me to get the final typeset version impacts-ASCO2011-author-personal.pdf).
Jebalia, M., A. Auger and N. Hansen (2011). Log-Linear Convergence and Divergence of the Scale-Invariant (1+1)-ES in Noisy Environments, Algorithmica, 59(3), pp. 425-460 (paper
draft in pdf, bibtex).
Suttorp, T., N. Hansen and C. Igel (2009). Efficient Covariance
Matrix Update for Variable Metric Evolution Strategies, Machine
Learning, 75, pp. 167-197; (abstract & erratum, paper
in pdf 1MB, bibtex).
Glass, C.W., A.R. Oganov and N. Hansen (2006). USPEX - evolutionary
crystal structure prediction.
Computer Physics Communications, 175, pp. 713-720;
(abstract, paper in
pdf, bibtex).
Hansen, N., D.V. Arnold and A. Auger (2015).
Evolution Strategies. In Janusz Kacprzyk and Witold Pedrycz (Eds.): Handbook of Computational Intelligence, Springer, Chapter 44, pp.871-898 (pdf).
Auger, A. and N. Hansen (2011).
Theory of Evolution Strategies: A New Perspective. In A. Auger and B. Doerr, eds.: Theory of Randomized Search Heuristics: Foundations and Recent Developments. World Scientific Publishing, pp. 289-325 (paper and erratum in pdf, bibtex).
Collette, Y., N. Hansen and G. Pujol (2009). Vers une Programmation
Orientée Objet des Optimiseurs. Chapter 7 in Optimisation
multidisciplinaire en mécanique 2. Réduction de
modèles, robustesse, fiabilité, réalisations
logicielles, series Méthodes Numériques
en Mécanique, Hermes Science & Lavoisier, ISBN 978-2-7462-2196-3;
(draft in pdf 790kB).
Keijzer, M., G. Antoniol, C.B. Congdon, K. Deb, B. Doerr, N. Hansen,
J.H. Holmes, G.S. Hornby, D. Howard, J. Kennedy, S. Kumar, F.G. Lobo,
J.F. Miller, J. Moore, F. Neumann, M. Pelikan,
J. Pollack, K. Sastry, K. Stanley, A. Stoica,
E-G. Talbi, I. Wegener (eds, 2008). GECCO Genetic and
Evolutionary Computation Conference, Proceedings, ACM, 2008.
Hansen, N. (2006). The CMA Evolution Strategy: A Comparing Review.
In J.A. Lozano, P. Larrañga, I. Inza and E. Bengoetxea (eds.).
Towards a new evolutionary computation. Advances in estimation of
distribution algorithms. pp. 75-102, Springer; (abstract and erratum,
paper in pdf 1.5MB, bibtex).
Books, Monographs
Hansen, N. (2010). Variable Metrics in Evolutionary Computation. Habilitation a diriger des recherches,
University Paris-Sud (pdf).
Hansen, N. (1998).Verallgemeinerte individuelle Schrittweitenregelung in der
Evolutionsstrategie. Eine Untersuchung zur entstochastisierten,
koordinatensystemunabhängigen Adaptation der Mutationsverteilung.
PhD
thesis, D83, Technical University Berlin, ISBN 3-933346-29-0. Berlin: Mensch
und Buch Verlag; (abstract, pdf 890kB, bibtex).
Schöneburg, E., N. Hansen and A. Gawelczyk (1992).
Neuronale
Netzwerke. Einführung, Überblick und Anwendungsmöglichkeiten.
Haar: Markt&Technik Verlag. Dritte, erweiterte Auflage.
Nikolaus Hansen (2019).
A global surrogate assisted CMA-ES.
In Genetic and Evolutionary Computation Conference (GECCO 2019), Proceedings, pp 664-672,
ACM (pdf, abstract&bibtex).
Touré, C, N. Hansen, A. Auger, D. Brockhoff (2019).
Uncrowded hypervolume improvement: COMO-CMA-ES and the sofomore framework.
In Genetic and Evolutionary Computation Conference (GECCO 2019), Proceedings, pp 638-646,
ACM (pdf, abstract&bibtex).
Tušar, T., D. Brockhoff, N. Hansen (2019).
Mixed-integer benchmark problems for single- and bi-objective optimization.
In Genetic and Evolutionary Computation Conference (GECCO 2019), Proceedings, pp 718-726,
ACM (pdf, abstract&paper).
Varelas, K., A. Auger, D. Brockhoff, N. Hansen, O. Elhara, Y. Semet, R. Kassab, F. Barbaresco (2018).
A Comparative Study of Large-scale Variants of CMA-ES.
PPSN XV 2018 - 15th International Conference on Parallel Problem Solving from Nature, Proceedings, LNCS 11101, pp.3-15,
Springer (abstract&paper).
Ait Elhara, O., A. Auger and N. Hansen (2016). Permuted Orthogonal Block-Diagonal Transformation Matrices for Large Scale Optimization Benchmarking.
In Genetic and Evolutionary Computation Conference (GECCO 2016), Proceedings, ACM (abstract & paper).
Akimoto, Y., and N. Hansen (2016).
Projection-Based Restricted Covariance Matrix Adaptation for High Dimension.
In Genetic and Evolutionary Computation Conference (GECCO 2016), Proceedings, ACM (abstract & paper).
Atamna, A., A. Auger, N. Hansen (2016).
Analysis of Linear Convergence of a (1 + 1)-ES with Augmented Lagrangian Constraint Handling.
In Genetic and Evolutionary Computation Conference (GECCO 2016), Proceedings, pp. 213-220, ACM.
Brockhoff, D., T.D. Tran, N. Hansen (2015). Benchmarking Numerical Multiobjective Optimizers Revisited.
In Genetic and Evolutionary Computation Conference (GECCO 2015), Proceedings, pp. 639-646, ACM (abstract & paper).
Akimoto, Y., A. Auger, and N. Hansen (2014). Comparison-Based Natural Gradient Optimization in High Dimension.
In Genetic and Evolutionary Computation Conference (GECCO 2014), Proceedings, ACM (pdf).
Chotard, A., A. Auger, and N. Hansen (2014). Markov Chain Analysis of Evolution Strategies on a Linear Constraint Optimization Problem. In Proceedings of the IEEE
Congress on Evolutionary Computation, CEC 2014 (abstract, bibtex, paper on HAL, abstract, paper on arXiv).
Akimoto, Y., A. Auger and N. Hansen (2012). Convergence of the continuous time trajectories of isotropic evolution strategies on monotonic C2-composite functions. In Parallel Problem Solving from Nature - PPSN XII, pp. 42-51, Springer (abstract and paper, paper on arxiv).
Chotard, A., A. Auger and N. Hansen (2012). Cumulative Step-Size Adaptation on Linear Functions. In Parallel Problem Solving from Nature - PPSN XII, pp. 72-81, Springer
(abstract and paper).
Arnold, D.V. and N. Hansen (2010). Active covariance matrix adaptation for the (1+1)-CMA-ES.
In Branke et al. (eds.), Genetic and Evolutionary Computation Conference GECCO 2010, Proceedings,
pp. 385-392, ACM (abstract, pdf, bibtex (see export), best paper award).
Voß, T., N. Hansen and C. Igel (2010). Improved step size adaptation for the MO-CMA-ES.
In Branke et al. (eds.), Genetic and Evolutionary Computation Conference GECCO 2010, Proceedings,
pp. 487-494, ACM (abstract, pdf, bibtex (see export)).
Voß, T., N. Hansen and C. Igel (2009). Recombination for
Learning Strategy Parameters in the MO-CMA-ES. In EMO
Conference on Evolutionary Multi-Criterion Optimization 2009,
Proceedings; (abstract, paper in pdf, bibtex).
Kern S., Hansen N. and Koumoutsakos P. (2007). Optimization of
Simulated Fish Swimming using Efficient Local Quadratic Meta-models
and Evolution Strategies. Eurogen 2007, Jyväskylä,
Finland, June 2007. (abstract, paper in pdf 1.5MB)
Igel, C., T. Suttorp and N. Hansen (2007).
Steady-state selection and efficient covariance matrix update in the
multi-objective CMA-ES.
In S. Obayashi et al. (eds.), Proceedings of the Fourth
International Conference on Evolutionary Multi-Criterion Optimization (EMO
2007), pp.171-185, Springer (paper in pdf).
Hansen, N., F. Gemperle, A. Auger and P. Koumoutsakos (2006). When Do
Heavy-Tail Distributions Help? In Ninth International
Conference on Parallel Problem Solving from Nature PPSN IX,
Proceedings, pp.62-71, Berlin: Springer; (abstract, paper draft pdf 5.7MB, bibtex).
Kern, S., N. Hansen and P. Koumoutsakos (2006). Local Meta-Models for
Optimization Using Evolution Strategies. In Ninth International
Conference on Parallel Problem Solving from Nature PPSN IX,
Proceedings, pp.939-948, Berlin: Springer; (abstract, paper draft in pdf).
Auger, A. and N. Hansen (2006). Reconsidering the Progress Rate
Theory for Evolution Strategies in Finite Dimensions. In
Proceedings of the Genetic and Evolutionary Computation Conference
(GECCO 2006), pp.445-452, ACM Press (abstract & erratum & bibtex, paper in pdf).
Ocenasek, J., S. Kern, N. Hansen and P. Koumoutsakos (2004). A
Mixed Bayesian Optimization Algorithm with Variance Adaptation. In
Eighth International Conference on Parallel Problem Solving from
Nature PPSN VIII, Proceedings, pp. 352-361, Berlin: Springer (paper in pdf).
Müller, S.D., N. Hansen and P. Koumoutsakos (2002). Increasing
the Serial and the Parallel Performance of the CMA-Evolution Strategy
with Large Populations. In Seventh International Conference on
Parallel Problem Solving from Nature PPSN VII, Proceedings,
pp. 422-431, Berlin: Springer; (abstract,
paper in pdf).
Hansen , N. (2000). Invariance, Self-Adaptation and Correlated
Mutations in Evolution Strategies. Sixth International Conference
on Parallel Problem Solving from Nature (PPSN VI), Proceedings,
pp. 355-364; (abstract,
paper in pdf,
paper in gzipped ps,
bibtex).
Ostermeier, A. and N. Hansen (1999).
An evolution strategy with coordinate system invariant adaptation of
arbitrary normal mutation distributions within the concept of mutative
strategy parameter control. In W.Banzhaf, J.Daida, A.Eiben,
M.H.Garzon, V.Honavar, M.Jakiela, R.E.Smith (eds.), GECCO-99
Proceedings of the Genetic and Evolutionary Computation
Conference,
pp.
902-909, San Francisco: Morgan Kaufmann Publishers;
(abstract,
paper in pdf,
paper in gzipped ps).
Hansen, N. and A. Ostermeier (1997).
Convergence properties of evolution strategies with the derandomized
covariance matrix adaptation: The (μ/μI,
λ)-ES. In
EUFIT'97, 5th Europ.Congr.on Intelligent Techniques and Soft
Computing, Proceedings, Aachen, pp. 650-654. Verlag Mainz,
Wissenschaftsverlag; (abstract,
paper in pdf,
paper in gzipped ps).
Hansen, N., A. Gawelczyk and A. Ostermeier (1995). Sizing the population
with respect to the local progress in (1, λ)-evolution strategies
a theoretical analysis. In 1995 IEEE International Conference on
Evolutionary Computation Proceedings, pp. 80-85; (abstract,
paper in pdf,
paper in gzipped ps).
Ostermeier, A., A. Gawelczyk and N. Hansen
(1994). Step-size adaptation based on non-local use of selection
information. In Y. Davidor, H.-P. Schwefel and R. Männer (eds.),
Parallel Problem Solving from Nature--PPSN IV, Proceedings,
Jerusalem, pp. 189-198. Springer; (paper in pdf 600kB).
More Proceedings
Nikolaus Hansen (2014). CMA-ES: A Function Value Free Second Order Optimization Method. In PGMO-COPI'14 Conference on Optimization and Practices in Industry, abstract and pdf.
Anne Auger, A., D. Brockhoff, and N. Hansen (2013). Benchmarking the local metamodel CMA-ES on the noiseless BBOB'2013 test bed. In Proceedings of the Fourteenth International Conference on Genetic and Evolutionary Computation Conference Companion, workshop on Black-Box Optimization Benchmarking (BBOB'2013), pp. 1225-1232, ACM (pdf).
Akimoto, Y., A. Auger, and N. Hansen (2012). Linear convergence proof for adaptive-ES algorithm via continuous-time approximation. In Proceedings of the 6th Evolutionary Computation Symposium, Nagano, Japan.
Brockhoff, D., A. Auger, and N. Hansen (2012). Comparing mirrored mutations and active covariance matrix adaptation in the IPOP-CMA-ES on the noiseless BBOB testbed. In Proceedings of the Fourteenth International Conference on Genetic and Evolutionary Computation Conference Companion, GECCO Companion '12, pp. 297-304, ACM (pdf).
Brockhoff, D., A. Auger, and N. Hansen (2012). On the impact of active covariance matrix adaptation in the CMA-ES with mirrored mutations and small initial population size on the noiseless BBOB testbed. In Proceedings of the Fourteenth International Conference on Genetic and Evolutionary Computation Conference Companion, GECCO Companion '12, pp. 291-296, ACM (pdf).
Brockhoff, D., A. Auger, and N. Hansen (2012). On the impact of a small initial population size in the IPOP active CMA-ES with mirrored mutations on the noiseless BBOB testbed. In Proceedings of the Fourteenth International Conference on Genetic and Evolutionary Computation Conference Companion, GECCO Companion '12, pp. 285-290, ACM (pdf).
Brockhoff, D., A. Auger, and N. Hansen (2012). On the effect of mirroring in the IPOP active CMA-ES on the noiseless BBOB testbed. In Proceedings of the Fourteenth International Conference on Genetic and Evolutionary Computation Conference Companion, GECCO Companion '12, pp. 277-284, ACM (pdf).
Collange, G., S. Reynaud and N. Hansen (2010). Covariance Matrix Adaptation Evolution Strategy for
Multidisciplinary Optimization of Expendable Launcher
Families. In 13th AIAA/ISSMO Multidisciplinary Analysis
Optimization Conference, Proceedings; (paper in pdf).
Auger, A., D. Brockhoff, N. Hansen (2010). Benchmarking the (1,4)-CMA-ES with Mirrored Sampling and Sequential Selection on the Noiseless BBOB-2010 Testbed. Workshop Proceedings of the GECCO Genetic and Evolutionary Computation Conference 2010, ACM, pp. 1617-1623 (abstract and pdf).
Auger, A., D. Brockhoff, N. Hansen (2010). Benchmarking the (1,4)-CMA-ES with Mirrored Sampling and Sequential Selection on the Noisy BBOB-2010 Testbed. Workshop Proceedings of the GECCO Genetic and Evolutionary Computation Conference 2010, ACM, pp. 1625-1631 (abstract and pdf).
Hansen, N., R. Ros (2010). Benchmarking a Weighted Negative Covariance Matrix
Update on the BBOB-2010 Noiseless Testbed. Workshop Proceedings of the GECCO Genetic and Evolutionary Computation Conference 2010, ACM, pp. 1673-1680
(paper in pdf).
Hansen, N., R. Ros (2010). Benchmarking a Weighted Negative Covariance Matrix
Update on the BBOB-2010 Noisy Testbed. Workshop Proceedings of the GECCO Genetic and Evolutionary Computation Conference 2010, ACM, pp. 1681-1687
(paper in pdf).
Auger, A and N. Hansen (2009).
Benchmarking the (1+1)-CMA-ES on the BBOB-2009 Function Testbed.
Workshop Proceedings of the GECCO Genetic and Evolutionary Computation
Conference, ACM, pp. 2459-2465.
Auger, A and N. Hansen (2009).
Benchmarking the (1+1)-CMA-ES on the BBOB-2009 Noisy Testbed.
Workshop Proceedings of the GECCO Genetic and Evolutionary Computation
Conference, ACM. pp. 2467-2471.
Auger, A., N. Hansen, J.M. Perez Zerpa, R. Ros and M. Schoenauer (2009).
Empirical comparisons of several derivative free optimization algorithms. In
Acte du 9ime colloque national en calcul des structures, Giens; (paper in pdf).
Hansen, N. (2009). Benchmarking a BI-Population CMA-ES on the
BBOB-2009 Function Testbed. Workshop Proceedings of the GECCO Genetic and Evolutionary Computation Conference, ACM, pp. 2389-2395
(abstract and pdf, erratum, source code, bibtex).
Hansen, N. (2009). Benchmarking a BI-Population CMA-ES on the
BBOB-2009 Noisy Testbed.
Workshop Proceedings of the GECCO Genetic and Evolutionary Computation
Conference, ACM, pp. 2397-2402
(abstract and pdf, erratum, bibtex).
Hansen, N. (2009). Benchmarking the Nelder-Mead Downhill Simplex
Algorithm With Many Local Restarts. Workshop Proceedings of the GECCO Genetic and Evolutionary Computation Conference, ACM, pp. 2403-2408 (abstract and pdf, bibtex).
Hansen, N., A.S.P. Niederberger, L. Guzzella and P. Koumoutsakos
(2008). Evolutionary Optimization of Feedback Controllers for
Thermoacoustic Instabilities. J.F.Morrison, D.M.Birch, and
P.Lavoie (eds.) IUTAM Symposium on Flow Control and MEMS,
Proceedings of the IUTAM Symposium held at the Royal Geographical
Society, 19-22 September 06, Springer, 2008 (abstract, paper draft in pdf).
Müller, S.D., N.N. Schraudolph, P. Koumoutsakos and N.Hansen
(2002). Step Size Adaptation in Evolution Strategies - Two
Approaches. In A. Barry (Ed.), Workshop on Learning and Adaptation
in Evolutionary Computation, Workshop Proceedings of the 2002 Genetic
and Evolutionary Computation Conference (GECCO-2002), pp. 161-164,
San Francisco: Morgan Kaufmann Publishers.
Rechenberg, I., F. Brand, N. Hansen, M. Herdy and A. Ostermeier (1995).
Theorie der Evolutionsstrategie Von der Zufallssuche zur intelligenten
Strategie. In G. Wolf, R. Schmidt and M. van der Meer (eds.), Tagungsband
zum Statusseminar des BMBF Bioinformatik 1995, 12484 Berlin, pp. 293-303.
Projektträger Informationstechnik des BMBF bei der DLR, Abteilung
Informationsverarbeitung.
Reports and Other Contributions
Auger A. and N. Hansen (2021).
A SIGEVO impact award for a paper arising from the COCO platform: a summary and beyond.
SIGEVOlution 13, 4, Article 1 (Winter 2020), 11 pages
(DOI:10.1145/3447929.3447930,
article online).
Hansen, N. (2016). The CMA Evolution Strategy: A Tutorial. ArXiv e-prints, arXiv:1604.00772.
Auger, A. and N. Hansen (2013). Linear convergence on positively homogeneous functions of a comparison based step-size adaptive randomized search: the (1+1) ES with generalized one-fifth success rule. CoRR, abs/1310.8397 (abstract, pdf, bibtex on arXiv).
Auger, A. and N. Hansen (2013). On proving linear convergence of comparison-based step-size adaptive randomized search on scaling-invariant functions via stability of markov chains. CoRR, abs/1310.7697 (abstract, pdf, bibtex on arXiv).
Ollivier, Y., L. Arnold, A. Auger, N. Hansen (2013). Information-Geometric Optimization Algorithms: A Unifying Picture via Invariance Principles. CoRR, abs/1106.3708v2 (abstract, pdf, bibtex on arXiv).
Hansen, N. (2011). A CMA-ES for Mixed-Integer Nonlinear Optimization. INRIA Research Report RR-7751 (abstract and pdf).
Hansen, N. (2011). Injecting External Solutions Into CMA-ES. INRIA Research Report RR-7748. CoRR, abs/1110.4181 (abstract, pdf, bibtex on arXiv).
Arnold, L., A. Auger, N. Hansen, Y. Ollivier (2011). Information-Geometric Optimization Algorithms: A Unifying Picture via Invariance Principles, technical report on HAL: hal-00601503, on arXiv: arXiv:1106.3708v1.
Hansen, N., A. Auger, S. Finck R. and Ros (2010),
Real-Parameter Black-Box Optimization Benchmarking 2010:
Experimental Setup, INRIA Research Report RR-7215 (abstract and report, bibtex).
Auger A., S. Finck, N. Hansen, R. Ros (2010). BBOB 2009: Comparison Tables of All Algorithms on All Noiseless Functions, INRIA Research Report RT-0383; (abstract/PDF/bibtex).
Auger A., S. Finck, N. Hansen, R. Ros (2010). BBOB 2009: Comparison Tables of All Algorithms on All Noisy Functions, INRIA Research Report RT-0383; (abstract/PDF/bibtex).
Finck, S., N. Hansen, R. Ros and A. Auger (2009),
Real-Parameter Black-Box Optimization Benchmarking 2009:
Presentation of the Noisy Functions, Research Center PPE, Report Number 2009/21 (pdf 20MB, bibtex).
Finck, S., N. Hansen, R. Ros and A. Auger (2009),
Real-Parameter Black-Box Optimization Benchmarking 2009:
Presentation of the Noiseless Functions, Research Center PPE, Report Number 2009/20 (pdf 13MB, bibtex).
Hansen, N., S. Finck, R. Ros and A. Auger (2009),
Real-Parameter Black-Box Optimization Benchmarking 2009:
Noisy Functions Definitions, INRIA Research Report RR-6869 (pdf, bibtex).
Hansen, N., S. Finck, R. Ros and A. Auger (2009),
Real-Parameter Black-Box Optimization Benchmarking 2009:
Noiseless Functions Definitions, INRIA Research Report RR-6829 (abstract and report, bibtex).
Hansen, N., A. Auger, S. Finck R. and Ros (2009),
Real-Parameter Black-Box Optimization Benchmarking 2009:
Experimental Setup, INRIA Research Report RR-6828 (abstract and report, bibtex).
Hansen, N. (2008).
CMA-ES with Two-Point Step-Size Adaptation.
INRIA Research Report RR-6527 (abstract and report).
Hansen, N. (2008).
Adaptive Encoding for Optimization.
INRIA Research Report RR-6518 (abstract and report).
Ros, R. and N. Hansen (2008).
A Simple Modification in CMA-ES Achieving Linear Time and Space Complexity.
INRIA Research Report RR-6498 (abstract and report).
Hansen, N, R. Ros, N. Mauny, M. Schoenauer and A. Auger (2008). PSO
Facing Non-Separable and Ill-Conditioned Problems. INRIA Research Report RR-6447 (abstract and report).
Suganthan, P.N., N. Hansen, J.J. Liang, K. Deb, Y. P. Chen, A. Auger, and S. Tiwari (2005). Problem definitions and evaluation criteria for the CEC 2005 special session on real-parameter
optimization. Technical report, Nanyang Technological University, Singapore and KanGAL
Report Number 2005005 (Kanpur Genetic Algorithms Laboratory, IIT Kanpur), May 2005 (report in pdf) .
Igel, C., N. Hansen and S. Roth (2005). The Multi-objective
Variable Metric Evolution Strategy, Part I. Technical Report,
IRINI-2001-04, Institut für Neuroinformatik (report in pdf).
Hansen, N., A. Ostermeier and A. Gawelczyk (1995). Über die Adaptation
von allgemeinen, Koordinatensystem-unabhängigen, normalverteilten
Mutationen in der Evolutionsstrategie: Die Erzeugendensystemadaptation.
Technischer Report TR-02-95, Institut für Bionik und Evolutionstechnik
der Technischen Universität Berlin;
(abstract,
paper in pdf,
paper in gzipped ps).
Ostermeier, A., A. Gawelczyk and N. Hansen (1993). A derandomized approach
to self adaptation of evolution strategies. Technischer Report TR-03-93,
Institut für Bionik und Evolutionstechnik der Technischen Universität
Berlin;
(abstract,
paper in gzipped ps).