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
More filters
Proceedings Article
Wasserstein Logistic Regression with Mixed Features
TL;DR: This paper shows that distributionally robust logistic regression with mixed features, despite amounting to an optimization problem of exponential size, admits a polynomial-time solution scheme, and develops a practically column-and-constraint approach that solves the problem as a sequence of polynometric-time solvable exponential conic programs.
Journal ArticleDOI
A robust framework for waste-to-energy technology selection: A case study in Nova Scotia, Canada
TL;DR: In this paper , a two-stage robust optimization model is proposed to minimize the total annual cost (including an environmental penalty) of a waste-to-energy facility, and the solution obtained from the robust model led to a 19.9% decrease in emissions compared to that of the deterministic model.
Proceedings ArticleDOI
Optimal Co-Allocation Plan of Dynamic Line Rating and FACTS for Wind Integration Considering Forecast Uncertainties
Lei You,Hui Ma,Tapan Kumar Saha +2 more
TL;DR: In this article, the authors investigated the combination of dynamic line rating (DLR) and FACTS to mitigate the network congestions due to wind integration and proposed a novel co-allocation model to select the optimal transmission lines for the installations of DLR.
Inverse Optimization, Incentive Design and Healthcare Policy
TL;DR: This dissertation presents mathematical models and algorithms that draw from optimization and statistics and are motivated by practical problems in operations management and suggests that accounting for cardiac arrest location uncertainty can lead to improved accessibility of defibrillators during cardiac arrest emergencies and the potential for improved survival outcomes.
Proceedings ArticleDOI
Adaptive Robust Unit Commitment in Coordinated Electricity and Natural Gas System
TL;DR: In this paper, a two-stage adaptive robust day-ahead unit commitment (UC) decision with the guarantee of gas flow feasibility is proposed, where column and constraint generation (C&CG) algorithm is used to solve the master problem.
References
More filters
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.