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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Prepositioning disaster relief supplies using robust optimization
TL;DR: A case study of the hurricane season in the Southeast US is used to gain insights on the effects of optimization criteria and critical model parameters to relief supply prepositioning strategy.
Journal ArticleDOI
Robust optimization for the vehicle routing problem with multiple deliverymen
TL;DR: In this paper, a static robust optimization approach is applied to obtain a robust counterpart formulation that captures the random nature of customer demand, which is used as a starting point for solving the robust counterpart.
Posted Content
Robust Defibrillator Deployment Under Cardiac Arrest Location Uncertainty via Row-and-Column Generation
TL;DR: This paper proposes a data-driven optimization model for deploying AEDs in public spaces while accounting for uncertainty in future cardiac arrest locations, which involves discretizing a continuous service area into a large set of scenarios, where the probability of cardiac arrest at each locat...
Journal ArticleDOI
Process optimization with consideration of uncertainties-An overview
TL;DR: An overview of the key contributions and recent advances in the field of process optimization under uncertainty over the past ten years is provided and three specific research areas are focused on, namely robust optimization, stochastic programming and chance constrained programming.
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.