Članki z zahtevami za javni dostop - Grani A. HanasusantoVeč o tem
Na voljo nekje: 22
Conic programming reformulations of two-stage distributionally robust linear programs over Wasserstein balls
GA Hanasusanto, D Kuhn
arXiv preprint arXiv:1609.07505, 2016
Zahteve: US National Science Foundation, Swiss National Science Foundation
K-adaptability in two-stage robust binary programming
GA Hanasusanto, D Kuhn, W Wiesemann
Operations Research 63 (4), 877-891, 2014
Zahteve: 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
Zahteve: Swiss National Science Foundation, UK Engineering and Physical Sciences …
Distributionally robust multi-item newsvendor problems with multimodal demand distributions
GA Hanasusanto, D Kuhn, SW Wallace, S Zymler
Mathematical Programming 152 (1), 1-32, 2015
Zahteve: UK Engineering and Physical Sciences Research Council
Ambiguous joint chance constraints under mean and dispersion information
GA Hanasusanto, V Roitch, D Kuhn, W Wiesemann
-, 2015
Zahteve: Swiss National Science Foundation, UK Engineering and Physical Sciences …
Data-driven inverse optimization with imperfect information
P Mohajerin Esfahani, S Shafieezadeh-Abadeh, GA Hanasusanto, ...
Zahteve: Swiss National Science Foundation
A comment on “Computational complexity of stochastic programming problems”
GA Hanasusanto, D Kuhn, W Wiesemann
Mathematical Programming, 2015
Zahteve: Swiss National Science Foundation, UK Engineering and Physical Sciences …
On data-driven prescriptive analytics with side information: a regularized nadaraya-watson approach
P Srivastava, Y Wang, GA Hanasusanto, CP Ho
Zahteve: US National Science Foundation
K-adaptability in two-stage distributionally robust binary programming
GA Hanasusanto, D Kuhn, W Wiesemann
Operations Research Letters, 2015
Zahteve: Swiss National Science Foundation, UK Engineering and Physical Sciences …
Optimal residential battery storage operations using robust data-driven dynamic programming
N Zhang, BD Leibowicz, GA Hanasusanto
IEEE Transactions on Smart Grid 11 (2), 1771-1780, 2019
Zahteve: US National Science Foundation
A robust spectral clustering algorithm for sub-Gaussian mixture models with outliers
PR Srivastava, P Sarkar, GA Hanasusanto
Operations Research 71 (1), 224-244, 2023
Zahteve: US National Science Foundation
Wasserstein Robust Classification with Fairness Constraints
Y Wang, VA Nguyen, GA Hanasusanto
arXiv preprint arXiv:2103.06828, 2021
Zahteve: US National Science Foundation
Robust quadratic programming with mixed-integer uncertainty
A Mittal, C Gokalp, GA Hanasusanto
arXiv preprint arXiv:1706.01949, 2017
Zahteve: US National Science Foundation
Finding minimum volume circumscribing ellipsoids using generalized copositive programming
A Mittal, GA Hanasusanto
Operations Research 70 (5), 2867-2882, 2022
Zahteve: US National Science Foundation
Improved conic reformulations for K-means clustering
MN Prasad, GA Hanasusanto
arXiv preprint arXiv:1706.07105, 2017
Zahteve: US National Science Foundation
Distributionally robust chance-constrained optimal transmission switching for renewable integration
Y Zhou, H Zhu, GA Hanasusanto
IEEE Transactions on Sustainable Energy 14 (1), 140-151, 2022
Zahteve: US National Science Foundation
Linearizing Bilinear Products of Shadow Prices and Dispatch Variables in Bilevel Problems for Optimal Power System Planning
N Laws, GA Hanasusanto
http://www.optimization-online.org/DB_HTML/2021/08/8561.html, 2021
Zahteve: US National Science Foundation, US Department of Energy
A decision rule approach for two-stage data-driven distributionally robust optimization problems with random recourse
X Fan, GA Hanasusanto
INFORMS Journal on Computing 36 (2), 526-542, 2024
Zahteve: US National Science Foundation
Transmission Switching Under Wind Uncertainty Using Linear Decision Rules
Y Zhou, H Zhu, GA Hanasusanto
IEEE General Meeting Power & Energy Society, arXiv: 1911.03027, 2020
Zahteve: US National Science Foundation
Data-Driven Stochastic Dual Dynamic Programming: Performance Guarantees and Regularization Schemes
H Park, Z Jia, GA Hanasusanto
Zahteve: US National Science Foundation
Podatke o objavi in financiranju samodejno določi računalniški program