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The Price of Robustness
A robust approach to solving linear optimization problems with uncertain data was proposed in the early 1970s and has recently been extensively studied and extended. Under this approach, we areExpand
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Robust discrete optimization and network flows
Abstract.We propose an approach to address data uncertainty for discrete optimization and network flow problems that allows controlling the degree of conservatism of the solution, and isExpand
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Robust linear optimization under general norms
We explicitly characterize the robust counterpart of a linear programming problem with uncertainty set described by an arbitrary norm. Our approach encompasses several approaches from the literatureExpand
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Distributionally Robust Convex Optimization
Distributionally robust optimization is a paradigm for decision making under uncertainty where the uncertain problem data are governed by a probability distribution that is itself subject toExpand
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Distributionally Robust Optimization and Its Tractable Approximations
In this paper we focus on a linear optimization problem with uncertainties, having expectations in the objective and in the set of constraints. We present a modular framework to obtain an approximateExpand
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Tractable Approximations to Robust Conic Optimization Problems
In earlier proposals, the robust counterpart of conic optimization problems exhibits a lateral increase in complexity, i.e., robust linear programming problems (LPs) become second order cone problemsExpand
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A Robust Optimization Perspective on Stochastic Programming
In this paper, we introduce an approach for constructing uncertainty sets for robust optimization using new deviation measures for random variables termed the forward and backward deviations. TheseExpand
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Risk Aversion in Inventory Management
Traditional inventory models focus on risk-neutral decision makers, i.e., characterizing replenishment strategies that maximize expected total profit, or equivalently, minimize expected total costExpand
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From CVaR to Uncertainty Set: Implications in Joint Chance-Constrained Optimization
We review and develop different tractable approximations to individual chance-constrained problems in robust optimization on a variety of uncertainty sets and show their interesting connections withExpand
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Satisficing Measures for Analysis of Risky Positions
In this work we introduce a class of measures for evaluating the quality of financial positions based on their ability to achieve desired financial goals. In the spirit of Simon (Simon, H. A. 1959.Expand
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