Hans-Georg Beyer
Hans-Georg Beyer
Professor, FH Vorarlberg
Verified email at fhv.at
TitleCited byYear
Evolution strategies–A comprehensive introduction
HG Beyer, HP Schwefel
Natural computing 1 (1), 3-52, 2002
23042002
Robust optimization–a comprehensive survey
HG Beyer, B Sendhoff
Computer methods in applied mechanics and engineering 196 (33-34), 3190-3218, 2007
14102007
The theory of evolution strategies
HG Beyer
Springer Science & Business Media, 2013
10662013
Self-adaptive genetic algorithms with simulated binary crossover
K Deb, HG Beyer
Evolutionary Computation 9 (2), 197-221, 2001
4112001
On self-adaptive features in real-parameter evolutionary algorithms
HG Beyer, K Deb
IEEE Transactions on evolutionary computation 5 (3), 250-270, 2001
3232001
Toward a theory of evolution strategies: Self-adaptation
HG Beyer
Evolutionary Computation 3 (3), 311-347, 1995
2741995
Evolutionary algorithms in noisy environments: Theoretical issues and guidelines for practice
HG Beyer
Computer methods in applied mechanics and engineering 186 (2-4), 239-267, 2000
2732000
Toward a theory of evolution strategies: On the benefits of sex—the (μ/μ, λ) theory
HG Beyer
Evolutionary Computation 3 (1), 81-111, 1995
2341995
Self-adaptation in evolutionary algorithms
S Meyer-Nieberg, HG Beyer
Parameter setting in evolutionary algorithms, 47-75, 2007
2072007
Noisy optimization with evolution strategies
DV Arnold
Springer Science & Business Media, 2012
1722012
Toward a Theory of Evolution Strategies: Some Asymptotical Results from the (1,+ λ)-Theory
HG Beyer
Evolutionary computation 1 (2), 165-188, 1993
1681993
How to analyse evolutionary algorithms
HG Beyer, HP Schwefel, I Wegener
Theoretical Computer Science 287 (1), 101-130, 2002
1612002
Benchmark generator for CEC 2009 competition on dynamic optimization
C Li, S Yang, TT Nguyen, EL Yu, X Yao, Y Jin, HG Beyer, PN Suganthan
1582008
Toward a theory of evolution strategies: The (μ, λ)-theory
HG Beyer
Evolutionary Computation 2 (4), 381-407, 1994
1241994
An alternative explanation for the manner in which genetic algorithms operate
HG Beyer
BioSystems 41 (1), 1-15, 1997
1141997
Covariance matrix adaptation revisited–the CMSA evolution strategy–
HG Beyer, B Sendhoff
International Conference on Parallel Problem Solving from Nature, 123-132, 2008
1132008
A comparison of evolution strategies with other direct search methods in the presence of noise
DV Arnold, HG Beyer
Computational Optimization and Applications 24 (1), 135-159, 2003
1092003
Thresholding-a selection operator for noisy ES
S Markon, DV Arnold, T Back, T Beielstein, HG Beyer
Proceedings of the 2001 Congress on Evolutionary Computation (IEEE Cat. No …, 2001
1032001
Self-adaptation in real-parameter genetic algorithms with simulated binary crossover
K Deb, HG Beyer
Proceedings of the 1st Annual Conference on Genetic and Evolutionary …, 1999
931999
A general noise model and its effects on evolution strategy performance
DV Arnold, HG Beyer
IEEE Transactions on Evolutionary Computation 10 (4), 380-391, 2006
862006
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