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Tobias Wagner
Tobias Wagner
Institute of Machining Technology (ISF), TU Dortmund
Dirección de correo verificada de isf.de - Página principal
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Pareto-, Aggregation-, and Indicator Based Methods in Many Objective Optimization
T Wagner, N Beume, B Naujoks
Proc. Int'l. Conf. Evolutionary multi-criterion optimization (EMO 2007), 2007
5682007
A benchmark of kriging-based infill criteria for noisy optimization
V Picheny, T Wagner, D Ginsbourger
Structural and multidisciplinary optimization 48, 607-626, 2013
4162013
Multiobjective optimization on a limited budget of evaluations using model-assisted-metric selection
W Ponweiser, T Wagner, D Biermann, M Vincze
International conference on parallel problem solving from nature, 784-794, 2008
3362008
On the properties of the R2 indicator
D Brockhoff, T Wagner, H Trautmann
Proceedings of the 14th annual conference on Genetic and evolutionary …, 2012
2382012
On expected-improvement criteria for model-based multi-objective optimization
T Wagner, M Emmerich, A Deutz, W Ponweiser
Parallel Problem Solving from Nature, PPSN XI: 11th International Conference …, 2010
1662010
Integration of preferences in hypervolume-based multiobjective evolutionary algorithms by means of desirability functions
T Wagner, H Trautmann
Evolutionary Computation, IEEE Transactions on 14 (5), 688-701, 2010
1342010
R2-EMOA: Focused multiobjective search using R2-indicator-based selection
H Trautmann, T Wagner, D Brockhoff
Learning and Intelligent Optimization: 7th International Conference, LION 7 …, 2013
1182013
Clustered multiple generalized expected improvement: A novel infill sampling criterion for surrogate models
W Ponweiser, T Wagner, M Vincze
2008 IEEE congress on evolutionary computation (IEEE world congress on …, 2008
1102008
2 indicator-based multiobjective search
D Brockhoff, T Wagner, H Trautmann
Evolutionary computation 23 (3), 369-395, 2015
972015
Model-based multi-objective optimization: taxonomy, multi-point proposal, toolbox and benchmark
D Horn, T Wagner, D Biermann, C Weihs, B Bischl
International Conference on Evolutionary Multi-Criterion Optimization, 64-78, 2015
872015
Evolutionary optimization of dynamic multiobjective functions
J Mehnen, G Rudolph, T Wagner
2nd Italian Workshop on Evolutionary Computation (2a Giornata di Studio …, 2006
762006
Statistical methods for convergence detection of multi-objective evolutionary algorithms
H Trautmann, T Wagner, B Naujoks, M Preuss, J Mehnen
Evolutionary computation 17 (4), 493-509, 2009
602009
A taxonomy of online stopping criteria for multi-objective evolutionary algorithms
T Wagner, H Trautmann, L Martí
Evolutionary Multi-Criterion Optimization: 6th International Conference, EMO …, 2011
572011
Efficient multi-criteria optimization on noisy machine learning problems
P Koch, T Wagner, MTM Emmerich, T Bäck, W Konen
Applied Soft Computing 29, 357-370, 2015
522015
OCD: Online convergence detection for evolutionary multi-objective algorithms based on statistical testing
T Wagner, H Trautmann, B Naujoks
International Conference on Evolutionary Multi-Criterion Optimization, 198-215, 2009
512009
Preference Articulation by Means of the R2 Indicator
T Wagner, H Trautmann, D Brockhoff
Evolutionary Multi-Criterion Optimization: 7th International Conference, EMO …, 2013
452013
Empirical modeling of hard turning of AISI 6150 steel using design and analysis of computer experiments
B Sieben, T Wagner, D Biermann
Production Engineering 4, 115-125, 2010
432010
A case study on multi-criteria optimization of an event detection software under limited budgets
M Zaefferer, T Bartz-Beielstein, B Naujoks, T Wagner, M Emmerich
Evolutionary Multi-Criterion Optimization: 7th International Conference, EMO …, 2013
332013
Online convergence detection for evolutionary multi-objective algorithms revisited
T Wagner, H Trautmann
IEEE Congress on Evolutionary Computation, 1-8, 2010
292010
Biobjective performance assessment with the COCO platform
D Brockhoff, T Tušar, D Tušar, T Wagner, N Hansen, A Auger
arXiv preprint arXiv:1605.01746, 2016
262016
El sistema no puede realizar la operación en estos momentos. Inténtalo de nuevo más tarde.
Artículos 1–20