Articles with public access mandates - Wolfram WiesemannLearn more
Not available anywhere: 1
The robust capacitated vehicle routing problem under demand uncertainty
CE Gounaris, W Wiesemann, CA Floudas
Operations Research 61 (3), 677-693, 2013
Mandates: UK Engineering and Physical Sciences Research Council
Available somewhere: 36
Distributionally robust convex optimization
W Wiesemann, D Kuhn, M Sim
Operations research 62 (6), 1358-1376, 2014
Mandates: UK Engineering and Physical Sciences Research Council, National Research …
K-Adaptability in Two-Stage Robust Binary Programming
GA Hanasusanto, D Kuhn, W Wiesemann
Operations Research 63 (4), 877-891, 2015
Mandates: UK Engineering and Physical Sciences Research Council
Generalized decision rule approximations for stochastic programming via liftings
A Georghiou, W Wiesemann, D Kuhn
Mathematical Programming 152, 301-338, 2015
Mandates: UK Engineering and Physical Sciences Research Council
A distributionally robust perspective on uncertainty quantification and chance constrained programming
GA Hanasusanto, V Roitch, D Kuhn, W Wiesemann
Mathematical Programming 151, 35-62, 2015
Mandates: Swiss National Science Foundation, UK Engineering and Physical Sciences …
Data-driven chance constrained programs over Wasserstein balls
Z Chen, D Kuhn, W Wiesemann
Operations Research 72 (1), 410-424, 2024
Mandates: Swiss National Science Foundation, UK Engineering and Physical Sciences …
Ambiguous joint chance constraints under mean and dispersion information
GA Hanasusanto, V Roitch, D Kuhn, W Wiesemann
Operations Research 65 (3), 751-767, 2017
Mandates: Swiss National Science Foundation, UK Engineering and Physical Sciences …
Robust dual dynamic programming
A Georghiou, A Tsoukalas, W Wiesemann
Operations Research 67 (3), 813-830, 2019
Mandates: UK Engineering and Physical Sciences Research Council
A comment on “computational complexity of stochastic programming problems”
GA Hanasusanto, D Kuhn, W Wiesemann
Mathematical Programming 159, 557-569, 2016
Mandates: Swiss National Science Foundation, UK Engineering and Physical Sciences …
K-adaptability in two-stage mixed-integer robust optimization
A Subramanyam, CE Gounaris, W Wiesemann
Mathematical Programming Computation 12, 193-224, 2020
Mandates: US National Science Foundation, UK Engineering and Physical Sciences …
The distributionally robust chance-constrained vehicle routing problem
S Ghosal, W Wiesemann
Operations Research 68 (3), 716-732, 2020
Mandates: UK Engineering and Physical Sciences Research Council
An adaptive memory programming framework for the robust capacitated vehicle routing problem
CE Gounaris, PP Repoussis, CD Tarantilis, W Wiesemann, CA Floudas
Transportation Science 50 (4), 1239-1260, 2016
Mandates: US National Science Foundation
Fast Bellman updates for robust MDPs
CP Ho, M Petrik, W Wiesemann
International Conference on Machine Learning, 1979-1988, 2018
Mandates: US National Science Foundation, UK Engineering and Physical Sciences …
Scenario reduction revisited: Fundamental limits and guarantees
N Rujeerapaiboon, K Schindler, D Kuhn, W Wiesemann
Mathematical Programming 191 (1), 207-242, 2022
Mandates: Swiss National Science Foundation, UK Engineering and Physical Sciences …
Partial policy iteration for l1-robust markov decision processes
CP Ho, M Petrik, W Wiesemann
Journal of Machine Learning Research 22 (275), 1-46, 2021
Mandates: US National Science Foundation, National Natural Science Foundation of China …
K-adaptability in two-stage distributionally robust binary programming
GA Hanasusanto, D Kuhn, W Wiesemann
Operations Research Letters 44 (1), 6-11, 2016
Mandates: Swiss National Science Foundation, UK Engineering and Physical Sciences …
Distributionally robust mechanism design
Ç Koçyiğit, G Iyengar, D Kuhn, W Wiesemann
Management Science 66 (1), 159-189, 2020
Mandates: Swiss National Science Foundation, UK Engineering and Physical Sciences …
On linear optimization over Wasserstein balls
MC Yue, D Kuhn, W Wiesemann
Mathematical Programming 195 (1), 1107-1122, 2022
Mandates: Swiss National Science Foundation, UK Engineering and Physical Sciences …
“Dice”-sion–making under uncertainty: when can a random decision reduce risk?
E Delage, D Kuhn, W Wiesemann
Management Science 65 (7), 3282-3301, 2019
Mandates: Swiss National Science Foundation, Natural Sciences and Engineering Research …
Size matters: Cardinality-constrained clustering and outlier detection via conic optimization
N Rujeerapaiboon, K Schindler, D Kuhn, W Wiesemann
SIAM Journal on Optimization 29 (2), 1211-1239, 2019
Mandates: Swiss National Science Foundation, UK Engineering and Physical Sciences …
Publication and funding information is determined automatically by a computer program