Bernhard Sendhoff
Bernhard Sendhoff
Honda Research Institute Europe
Verified email at honda-ri.de
TitleCited byYear
Robust optimization–a comprehensive survey
HG Beyer, B Sendhoff
Computer methods in applied mechanics and engineering 196 (33-34), 3190-3218, 2007
14542007
A framework for evolutionary optimization with approximate fitness functions
Y Jin, M Olhofer, B Sendhoff
IEEE Transactions on evolutionary computation 6 (5), 481-494, 2002
5902002
A reference vector guided evolutionary algorithm for many-objective optimization
R Cheng, Y Jin, M Olhofer, B Sendhoff
IEEE Transactions on Evolutionary Computation 20 (5), 773-791, 2016
3382016
Pareto-based multiobjective machine learning: An overview and case studies
Y Jin, B Sendhoff
IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and …, 2008
3172008
A critical survey of performance indices for multi-objective optimisation
T Okabe, Y Jin, B Sendhoff
The 2003 Congress on Evolutionary Computation, 2003. CEC'03. 2, 878-885, 2003
3052003
Generalizing surrogate-assisted evolutionary computation
D Lim, Y Jin, YS Ong, B Sendhoff
IEEE Transactions on Evolutionary Computation 14 (3), 329-355, 2009
2982009
Dynamic weighted aggregation for evolutionary multi-objective optimization: Why does it work and how?
Y Jin, M Olhofer, B Sendhoff
Proceedings of the 3rd Annual Conference on Genetic and Evolutionary …, 2001
2632001
Trade-off between performance and robustness: an evolutionary multiobjective approach
Y Jin, B Sendhoff
international conference on Evolutionary Multi-Criterion Optimization, 237-251, 2003
2502003
On generating FC/sup 3/fuzzy rule systems from data using evolution strategies
Y Jin, W Von Seelen, B Sendhoff
IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) 29 …, 1999
2431999
Optimization of micro heat exchanger: CFD, analytical approach and multi-objective evolutionary algorithms
K Foli, T Okabe, M Olhofer, Y Jin, B Sendhoff
International Journal of Heat and Mass Transfer 49 (5-6), 1090-1099, 2006
2352006
Efficient hierarchical parallel genetic algorithms using grid computing
D Lim, YS Ong, Y Jin, B Sendhoff, BS Lee
Future Generation Computer Systems 23 (4), 658-670, 2007
2292007
Combining model-based and genetics-based offspring generation for multi-objective optimization using a convergence criterion
A Zhou, Y Jin, Q Zhang, B Sendhoff, E Tsang
2006 IEEE International Conference on Evolutionary Computation, 892-899, 2006
1922006
On evolutionary optimization with approximate fitness functions
Y Jin, M Olhofer, B Sendhoff
Proceedings of the 2nd Annual Conference on Genetic and Evolutionary …, 2000
1672000
Adapting weighted aggregation for multiobjective evolution strategies
Y Jin, T Okabe, B Sendho
International Conference on Evolutionary Multi-Criterion Optimization, 96-110, 2001
1662001
Neural network regularization and ensembling using multi-objective evolutionary algorithms
Y Jin, T Okabe, B Sendhoff
Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No …, 2004
1592004
Reducing fitness evaluations using clustering techniques and neural network ensembles
Y Jin, B Sendhoff
Genetic and Evolutionary Computation Conference, 688-699, 2004
1572004
Constructing dynamic optimization test problems using the multi-objective optimization concept
Y Jin, B Sendhoff
Workshops on Applications of Evolutionary Computation, 525-536, 2004
1552004
Prediction-based population re-initialization for evolutionary dynamic multi-objective optimization
A Zhou, Y Jin, Q Zhang, B Sendhoff, E Tsang
International Conference on Evolutionary Multi-Criterion Optimization, 832-846, 2007
1372007
On test functions for evolutionary multi-objective optimization
T Okabe, Y Jin, M Olhofer, B Sendhoff
International Conference on Parallel Problem Solving from Nature, 792-802, 2004
1322004
Covariance matrix adaptation revisited–the CMSA evolution strategy–
HG Beyer, B Sendhoff
International Conference on Parallel Problem Solving from Nature, 123-132, 2008
1172008
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