Tea Tušar
Cited by
Cited by
Differential evolution for multiobjective optimization
T Robič, B Filipič
International conference on evolutionary multi-criterion optimization, 520-533, 2005
Differential evolution versus genetic algorithms in multiobjective optimization
T Tušar, B Filipič
International Conference on Evolutionary Multi-Criterion Optimization, 257-271, 2007
Visualization of Pareto front approximations in evolutionary multiobjective optimization: A critical review and the prosection method
T Tušar, B Filipič
IEEE Transactions on Evolutionary Computation 19 (2), 225-245, 2014
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, 1-31, 2020
A comparative study of stochastic optimization methods in electric motor design
T Tušar, P Korošec, G Papa, B Filipič, J Šilc
Applied Intelligence 27 (2), 101-111, 2007
COCO: Performance assessment
N Hansen, A Auger, D Brockhoff, D Tušar, T Tušar
arXiv preprint arXiv:1605.03560, 2016
GP-DEMO: differential evolution for multiobjective optimization based on Gaussian process models
M Mlakar, D Petelin, T Tušar, B Filipič
European Journal of Operational Research 243 (2), 347-361, 2015
Data management in the mirabel smart grid system
M Boehm, L Dannecker, A Doms, E Dovgan, B Filipič, U Fischer, ...
Proceedings of the 2012 Joint EDBT/ICDT Workshops, 95-102, 2012
COCO: the bi-objective black box optimization benchmarking (bbob-biobj) test suite
T Tušar, D Brockhoff, N Hansen, A Auger
ArXiv e-prints, 2016
COCO: A platform for comparing continuous optimizers in a black-box setting. ArXiv e-prints
N Hansen, A Auger, O Mersmann, T Tušar, D Brockhoff
arXiv preprint arXiv:1603.08785, 2016
COCO: The experimental procedure
N Hansen, T Tusar, O Mersmann, A Auger, D Brockhoff
arXiv preprint arXiv:1603.08776, 2016
Preliminary numerical experiments in multiobjective optimization of a metallurgical production process
B Filipic, T Tušar, E Laitinen
Informatica 31 (2), 2007
Comparing solutions under uncertainty in multiobjective optimization
M Mlakar, T Tušar, B Filipič
Mathematical Problems in Engineering 2014, 2014
Visualizing 4D approximation sets of multiobjective optimizers with prosections
T Tušar, B Filipič
Proceedings of the 13th annual conference on Genetic and evolutionary …, 2011
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
Discovering comfortable driving strategies using simulation-based multiobjective optimization
E Dovgan, T Tušar, M Javorski, B Filipič
Informatica 36 (3), 2012
Intelligent High-Security Access Control
M Gams, T Tušar
Informatica 31 (4), 2007
A study of overfitting in optimization of a manufacturing quality control procedure
T Tušar, K Gantar, V Koblar, B Ženko, B Filipič
Applied Soft Computing 59, 77-87, 2017
Discovering driving strategies with a multiobjective optimization algorithm
E Dovgan, M Javorski, T Tušar, M Gams, B Filipič
Applied soft computing 16, 50-62, 2014
Optimizing accuracy and size of decision trees
T Tušar
Sixteenth International Electrotechnical and Computer Science Conference-ERK …, 2007
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