Distributionally robust two-stage stochastic programming
Distributionally robust optimization is a popular modeling paradigm in which the underlying
distribution of the random parameters in a stochastic optimization model is unknown …
distribution of the random parameters in a stochastic optimization model is unknown …
Stochastic decomposition method for two-stage distributionally robust linear optimization
H Gangammanavar, M Bansal - SIAM Journal on Optimization, 2022 - SIAM
In this paper, we present a sequential sampling-based algorithm for the two-stage
distributionally robust linear programming (2-DRLP) models. The 2-DRLP models are …
distributionally robust linear programming (2-DRLP) models. The 2-DRLP models are …
Data-driven distributionally robust optimization for railway timetabling problem
Unpredictable disturbances that occur when the train is running often make the actual
timetable deviate from the planned timetable and deteriorate service quality for passengers …
timetable deviate from the planned timetable and deteriorate service quality for passengers …
Distributionally robust optimization for pre-disaster facility location problem with 3D printing
The ongoing advancement of 3D printing technology provides an innovative approach to
addressing challenges in disaster relief operations. By utilizing a variety of printing …
addressing challenges in disaster relief operations. By utilizing a variety of printing …
Bidding Strategy for Hybrid PV-BESS Plants via Knowledge-Data-Complementary Learning
The hybrid PV-BESS plant (HPP), integrating PV and BESS, can gain revenue by performing
energy arbitrage in low-carbon power systems. However, multiple operational uncertainties …
energy arbitrage in low-carbon power systems. However, multiple operational uncertainties …
System Restoration for Low-inertia Power Systems Incorporating Fast Frequency Response via Distributionally Robust Optimization
Z Qin, Y Li, X Chen, H Liu - IEEE Transactions on Power …, 2024 - ieeexplore.ieee.org
The high share of renewable energy sources (RESs) in power system creates inertia
shortfalls, posing challenges in system restoration after a major outage due to lower system …
shortfalls, posing challenges in system restoration after a major outage due to lower system …
Distributionally Robust Chance-Constrained Line Planning for Railway Systems Under Passenger Demand Uncertainty
L Liu, W Yang, S Song, Y Zhang - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
In a railway network, making a line plan is a critical optimization problem that determines the
daily transportation capacity of the network, aiming at aligning it with passenger demand …
daily transportation capacity of the network, aiming at aligning it with passenger demand …
PolieDRO: a novel classification and regression framework with non-parametric data-driven regularization
T Gutierrez, D Valladão, BK Pagnoncelli - Machine Learning, 2024 - Springer
PolieDRO is a novel analytics framework for classification and regression that harnesses the
power and flexibility of data-driven distributionally robust optimization (DRO) to circumvent …
power and flexibility of data-driven distributionally robust optimization (DRO) to circumvent …
On affine policies for wasserstein distributionally robust unit commitment
his paper proposes a unit commitment (UC) model based on data-driven Wasserstein
distributionally robust optimization (WDRO) for power systems under uncertainty of …
distributionally robust optimization (WDRO) for power systems under uncertainty of …
[图书][B] A column generation scheme for distributionally robust multi-item newsvendor problems
S Wang, E Delage - 2021 - tintin.hec.ca
In this paper, we study a distributionally robust multi-item newsvendor problem, where the
demand distribution is unknown but specified with a general event-wise ambiguity set. Using …
demand distribution is unknown but specified with a general event-wise ambiguity set. Using …