Journal ArticleDOI
Solving two-stage robust optimization problems using a column-and-constraint generation method
TLDR
A computational study on a two-stage robust location-transportation problem shows that the column-and-constraint generation algorithm performs an order of magnitude faster than existing Benders-style cutting plane methods.About:
This article is published in Operations Research Letters.The article was published on 2013-09-01. It has received 1010 citations till now. The article focuses on the topics: Robust optimization & Cutting-plane method.read more
Citations
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Reliable Power System Planning and Operations through Robust Optimization
TL;DR: The Defender-Attacker-Defender Model for Power Grid Protection, a model for protection for attackers and defenders using a network-based approach, and some of the principles behind that model are described.
Journal ArticleDOI
Robust Investment for Demand Response in a Distribution Network considering Wind Power and Load Demand Uncertainties
TL;DR: In this paper, a novel optimization model for demand response facility (DRF) investment to determine the DR sizing and siting is proposed, and robust optimization is adopted to maintain overall economic benefit and distribution network operation security.
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Risk-Averse Stochastic Programming vs. Adaptive Robust Optimization: A Virtual Power Plant Application
TL;DR: In this article , the authors compared risk-averse optimization methods to address the self-scheduling and market involvement of a virtual power plant (VPP), where the decision making problem of the VPP involves uncertainty in the wind speed and electricity price forecast.
Two-Stage Robust Optimization with Decision Dependent Uncertainty
TL;DR: A systematic study to handle the type of decision dependent uncertainties (DDUs) in two-stage robust optimization (RO) and a counterintuitive discovery that converting a DIU set into a DDU set by making use of “deep knowledge” and then computing the resulting DDU-based formulation may lead to a significant improvement.
References
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Journal ArticleDOI
The Price of Robustness
Dimitris Bertsimas,Melvyn Sim +1 more
TL;DR: In this paper, the authors propose an approach that attempts to make this trade-off more attractive by flexibly adjusting the level of conservatism of the robust solutions in terms of probabilistic bounds of constraint violations.
The price of the robustness
D Bertsimas,M Sim +1 more
TL;DR: An approach is proposed that flexibly adjust the level of conservatism of the robust solutions in terms of probabilistic bounds of constraint violations, and an attractive aspect of this method is that the new robust formulation is also a linear optimization problem, so it naturally extend to discrete optimization problems in a tractable way.
Journal ArticleDOI
Robust Convex Optimization
Aharon Ben-Tal,Arkadi Nemirovski +1 more
TL;DR: If U is an ellipsoidal uncertainty set, then for some of the most important generic convex optimization problems (linear programming, quadratically constrained programming, semidefinite programming and others) the corresponding robust convex program is either exactly, or approximately, a tractable problem which lends itself to efficientalgorithms such as polynomial time interior point methods.
Journal ArticleDOI
Generalized Benders decomposition
TL;DR: In this paper, the extremal value of the linear program as a function of the parameterizing vector and the set of values of the parametric vector for which the program is feasible were derived using linear programming duality theory.