Wolfram Wiesemann
Wolfram Wiesemann
Professor of Analytics and Operations, Imperial College Business School
Verified email at imperial.ac.uk - Homepage
Cited by
Cited by
Distributionally robust convex optimization
W Wiesemann, D Kuhn, M Sim
Operations Research 62 (6), 1358-1376, 2014
Primal and dual linear decision rules in stochastic and robust optimization
D Kuhn, W Wiesemann, A Georghiou
Mathematical Programming 130 (1), 177-209, 2011
Robust Markov decision processes
W Wiesemann, D Kuhn, B Rustem
Mathematics of Operations Research 38 (1), 153-183, 2013
The robust capacitated vehicle routing problem under demand uncertainty
CE Gounaris, W Wiesemann, CA Floudas
Operations Research 61 (3), 677-693, 2013
Generalized decision rule approximations for stochastic programming via liftings
A Georghiou, W Wiesemann, D Kuhn
Mathematical Programming 152 (1), 301-338, 2015
K-Adaptability in Two-Stage Robust Binary Programming
GA Hanasusanto, D Kuhn, W Wiesemann
Operations Research 63 (4), 877-891, 2015
A distributionally robust perspective on uncertainty quantification and chance constrained programming
GA Hanasusanto, V Roitch, D Kuhn, W Wiesemann
Mathematical Programming 151 (1), 35-62, 2015
Ambiguous joint chance constraints under mean and dispersion information
GA Hanasusanto, V Roitch, D Kuhn, W Wiesemann
Operations Research 65 (3), 751-767, 2017
Maximizing the net present value of a project under uncertainty
W Wiesemann, D Kuhn, B Rustem
European Journal of Operational Research 202 (2), 356-367, 2010
Pessimistic bilevel optimization
W Wiesemann, A Tsoukalas, PM Kleniati, B Rustem
SIAM Journal on Optimization 23 (1), 353-380, 2013
A stochastic programming approach for qos-aware service composition
W Wiesemann, R Hochreiter, D Kuhn
2008 Eighth IEEE International Symposium on Cluster Computing and the Grid …, 2008
SQPR: Stream query planning with reuse
E Kalyvianaki, W Wiesemann, QH Vu, D Kuhn, P Pietzuch
2011 IEEE 27th International Conference on Data Engineering, 840-851, 2011
Data-driven chance constrained programs over Wasserstein balls
Z Chen, D Kuhn, W Wiesemann
arXiv preprint arXiv:1809.00210, 2018
A comment on “computational complexity of stochastic programming problems”
GA Hanasusanto, D Kuhn, W Wiesemann
Mathematical Programming 159 (1), 557-569, 2016
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
Robust resource allocations in temporal networks
W Wiesemann, D Kuhn, B Rustem
Mathematical programming 135 (1), 437-471, 2012
Global optimisation of pessimistic bi-level problems
A Tsoukalas, W Wiesemann, B Rustem
Lectures on global optimization 55, 215-243, 2009
Robust growth-optimal portfolios
N Rujeerapaiboon, D Kuhn, W Wiesemann
Management Science 62 (7), 2090-2109, 2016
Robust dual dynamic programming
A Georghiou, A Tsoukalas, W Wiesemann
Operations Research 67 (3), 813-830, 2019
Iterated ants: An experimental study for the quadratic assignment problem
W Wiesemann, T Stützle
International Workshop on Ant Colony Optimization and Swarm Intelligence …, 2006
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