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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A Review of Wind Energy Output Simulation for New Power System Planning
TL;DR: In this paper , the authors present a simulation model of wind energy output for new power system planning based on probability and time series and discuss the characteristics of wind power output and the directions for further research in the future.
Journal ArticleDOI
A Mixed-Integer SDP Solution Approach to Distributionally Robust Unit Commitment with Second Order Moment Constraints
TL;DR: In this paper, a power system unit commitment (UC) problem considering uncertainties of renewable energy sources is investigated, through a distributionally robust optimization approach, where the first and second order moments of stochastic parameters are inferred from historical data, and then employed to model the set of probability distributions.
Journal ArticleDOI
Reliability-Based Expansion Planning Studies of Active Distribution Networks With Multiagents
Milad Kabirifar,Mahmud Fotuhi-Firuzabad,Moein Moeini-Aghtaie,Niloofar Pourghaderi,Mohammad Shahidehpour +4 more
TL;DR: In this article , a multi-agent framework is proposed to address the expansion planning problem in a restructured active distribution network, where the objective and techno-economic constraints of participating agents are addressed in the expansion plans of power network and DER assets as well as the DERs optimal operation management.
Journal ArticleDOI
Data-driven distributionally robust transmission expansion planning considering contingency-constrained generation reserve optimization
TL;DR: A two-stage data-driven distributionally robust transmission expansion planning model is proposed to incorporate the pre- and post-contingency generation reserve optimization, which strongly demonstrates the robustness and economic efficiency under bundled uncertainty.
Posted Content
Pareto Adaptive Robust Optimality via a Fourier-Motzkin Elimination Lens
TL;DR: It is argued that, unlike PARO, extant solution approaches -- including those that adopt Pareto Robust Optimality from static robust optimization -- could fail in ARO and yield solutions that can be Paredto dominated, and could lead to inefficiencies and suboptimal performance in practice.
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.