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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Real-time low-carbon scheduling for the wind–thermal–hydro-storage resilient power system using linear stochastic robust optimization
TL;DR: In this paper , a real-time low-carbon scheduling for the wind-thermal-hydro-storage integrated system is proposed, where the power imbalance caused by the uncertainty is neutralized by the synergetic linear decision of multiple resources.
Journal ArticleDOI
Data-driven Prediction of Relevant Scenarios for Robust Optimization
TL;DR: This paper proposes a data-driven heuristic to seed the iterative solution method with a set of starting scenarios that provide a strong lower bound early in the process, and result in considerably smaller overall solution times compared to other benchmark methods.
Posted Content
Resilient Unit Commitment for Day-ahead Market Considering Probabilistic Impacts of Hurricanes
TL;DR: In this paper, a resilient unit commitment (UC) problem is formulated as a two-stage robust optimization (RO) problem, in which the status, energy, and reserves of generators are pre-scheduled to minimize the operational cost, responding to the worst line failure scenario in the operating day.
Proceedings ArticleDOI
Research on Distributed Robust Optimization of Islanded Microgrids Based on Kullback–Leibler divergence
TL;DR: In this article , the authors proposed a method to measure probability distribution using Kullback-Leibler divergence and established a distributionally robust optimization based on the kullback Leibler divergences model.
Journal ArticleDOI
Unlock the Thermal Flexibility in Integrated Energy Systems: A Robust Nodal Pricing Approach for Thermal Loads
TL;DR: In this paper , a robust nodal pricing (RNP) model for thermal loads based on the Stackelberg game approach is proposed to incentivize the thermal flexibility of buildings under uncertainties, which adopts a bilevel framework in which the IES operator plays the leader at the upper level while the thermal load aggregators play the followers at the lower level.
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.