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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Journal ArticleDOI
Robust Line Hardening Strategies for Improving the Resilience of Distribution Systems With Variable Renewable Resources
TL;DR: The numerical results for the IEEE distribution test systems validate the effectiveness of the proposed model and reveal that distributed generation is critical in increasing the resilience of distribution systems corresponding to the worst N-k contingencies in provisional microgrids.
Journal ArticleDOI
A Stochastic Adaptive Robust Optimization Approach for the Offering Strategy of a Virtual Power Plant
Ana Baringo,Luis Baringo +1 more
TL;DR: In this paper, the authors propose a novel approach for the offering strategy of a virtual power plant that participates in the day-ahead and the real-time energy markets, where the uncertainty in the wind-power production and in the market prices using confidence bounds and scenarios, respectively, allows them to formul-ate the strategic offering problem as a stochastic adaptive robust optimization model.
Journal ArticleDOI
Data‐driven adaptive nested robust optimization: General modeling framework and efficient computational algorithm for decision making under uncertainty
Chao Ning,Fengqi You +1 more
TL;DR: A novel data-driven adaptive robust optimization framework that leverages big data in process industries is proposed and a Bayesian nonparametric model—the Dirichlet process mixture model—is adopted and combined with a variational inference algorithm to extract the information embedded within uncertainty data.
Journal ArticleDOI
Robust Defense Strategy for Gas–Electric Systems Against Malicious Attacks
TL;DR: In this article, the authors proposed a methodology to identify and protect vulnerable components of connected gas and electric infrastructures from malicious attacks, and to guarantee a resilient operation by deploying valid corrective actions, while accounting for the interdependence of the gas pipeline network and power transmission network.
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A survey of network interdiction models and algorithms
J. Cole Smith,Yongjia Song +1 more
TL;DR: This paper discusses the development of interdiction optimization models and algorithms, with an emphasis on mathematical programming techniques and future research challenges in the field, and examines contemporary interdictions problems involving incomplete information, information asymmetry, stochasticity and dynamic play.
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.