- W. Römisch and T. M. Surowiec: Asympyotic properties of
Monte Carlo methods in elliptic PDE-constrained optimization under uncertainty, Preprint
arXiv:2106347 and submitted.
- R. Henrion and W. Römisch:
Problem-based optimal scenario generation and reduction in stochastic programming, Mathematical Programming 191 (2022), 183--205
(published online: 4 October 2018),
doi: 10.1007/s10107-018-1337-6.
- M. Schmidt et al: Capacity Evaluation for Large-Scale
Gas Networks, in German Success Stories in Industrial Mathematics
(H.-G. Bock, K.-H. Küfer, P. Maass, A. Milde and V. Schulz eds.), Mathematics in Industry,
Springer, 2021, 23--28
- M. Hoffhues, W. Römisch and T. M. Surowiec: On
quantitative stability in infinite-dimensional optimization under uncertainty,
Optimization Letters 15 (2021), 2733--2756. doi: 10.1007/s11590-021-01707-2.
- H. Leövey and W. Römisch: Quasi-Monte
Carlo methods for two-stage stochastic mixed-integer programs,
Mathematical Programming 190 (2021), 361--392.
doi: 10.1007/s10107-020-01538-6.
- H. Leövey and W. Römisch: Randomized QMC methods for mixed-integer two-stage stochastic programs with application to electricity optimization, in Monte Carlo and Quasi-Monte Carlo Methods 2018
(B. Tuffin and P. L'Ecuyer eds.), Springer, 2020, 345--362.
- W. Römisch: Stochastic Programming: Approximations and
Scenarios, Expository Article, INFORMS Optimization Society, 2019.
- W. Römisch: Stochastic programming, scenario
generation in , in WileyStatsRef: Statistics Reference Online, John Wiley & Sons Ltd., 2018
(ISBN 9781118445112).
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Mathematical
Analysis and the Mathematics of Computation, Springer International Publishing, 2016,
ISBN 978-3-319-42753-9 (print), 978-3-319-42755-3 (e-book).
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Computational Optimization and Applications 65 (2016), 567--603.
last modified March 04, 2022