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Jan Schwientek
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2020 – today
- 2024
- [j7]David Mogalle
, Philipp Seufert, Jan Schwientek, Michael Bortz, Karl-Heinz Küfer:
Computing T-optimal designs via nested semi-infinite programming and twofold adaptive discretization. Comput. Stat. 39(5): 2451-2478 (2024) - 2022
- [j6]Holger Berthold, Holger Heitsch
On the algorithmic solution of optimization problems subject to probabilistic/robust (probust) constraints. Math. Methods Oper. Res. 96(1): 1-37 (2022) - [j5]Helene Krieg
Solving continuous set covering problems by means of semi-infinite optimization. Math. Methods Oper. Res. 96(1): 39-82 (2022) - [c3]David Mogalle, Philipp Seufert, Jan Schwientek, Michael Bortz, Karl-Heinz Küfer:
A Tri-Level Approach for T-Criterion-Based Model Discrimination. OR 2022: 87-93 - 2021
- [j4]Martin von Kurnatowski
Compensating Data Shortages in Manufacturing with Monotonicity Knowledge. Algorithms 14(12): 345 (2021) - [j3]Charlie Vanaret, Philipp Seufert, Jan Schwientek, Gleb Karpov, Gleb V. Ryzhakov, Ivan V. Oseledets, Norbert Asprion
Two-phase approaches to optimal model-based design of experiments: how many experiments and which ones? Comput. Chem. Eng. 146: 107218 (2021) - [j2]Jan Schwientek
A transformation-based discretization method for solving general semi-infinite optimization problems. Math. Methods Oper. Res. 93(1): 83-114 (2021)
2010 – 2019
- 2019
- [c2]Helene Krieg
Optimal Product Portfolio Design by Means of Semi-infinite Programming. OR 2019: 489-495 - [c1]Jan Schwientek, Charlie Vanaret, Johannes Höller, Patrick Schwartz, Philipp Seufert, Norbert Asprion, Roger Böttcher, Michael Bortz:
A Two-Phase Approach for Model-Based Design of Experiments Applied in Chemical Engineering. OR 2019: 513-519 - 2012
- [j1]Sabrina Haase, Philipp Süss
Radiofrequency ablation planning: An application of semi-infinite modelling techniques. Eur. J. Oper. Res. 218(3): 856-864 (2012)
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