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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Addressing the Conditional and Correlated Wind Power Forecast Errors in Unit Commitment by Distributionally Robust Optimization
TL;DR: A novel cutting plane algorithm that makes use of the extremal distributions identified from the second-stage semidefinite programming (SDP) problems is introduced and the advantage of the proposed model in capturing the spatiotemporal correlation in wind power generation, as well as the economic efficiency, and robustness of dispatch decisions is shown.
Journal ArticleDOI
Resilient Unit Commitment for Day-Ahead Market Considering Probabilistic Impacts of Hurricanes
TL;DR: A resilient unit commitment (UC) problem is formulated as a two-stage distributionally robust and robust optimization (DR&RO) problem, responding to the worst load forecasting and line failure scenario in the operating day.
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Day-Ahead Scheduling of Distribution Level Integrated Electricity and Natural Gas System Based on Fast-ADMM With Restart Algorithm
TL;DR: A day-ahead scheduling framework of integrated electricity and NG system (IENG) is proposed at a distribution level based on the fast alternating direction multiplier method with restart algorithm considering demand side response and uncertainties.
Journal ArticleDOI
Data-Driven Distributionally Robust Unit Commitment With Wasserstein Metric: Tractable Formulation and Efficient Solution Method
Xiaodong Zheng,Haoyong Chen +1 more
TL;DR: A novel cutting plane algorithm is proposed to solve the DRUC-dW problem much more efficiently than state-of-the-art and is an extension of the column-and-constraint generation method to the distributionally robust cases.
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Optimal coordinated operation of integrated natural gas and electric power systems: A review of modeling and solution methods
TL;DR: Analyzing the existing literature about the short-term optimal operation of integrated electrical-gas systems (IEGSs) and identifying the benefits of coordinated optimization compared to independent scheduling of the two sectors shows that lower operating costs and higher utilization of renewables are achieved by adopting fully integrated optimization strategies.
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.
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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.
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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.