Distributionally robust optimization. A review on theory and applications
From MaRDI portal
Publication:2074636
DOI10.3934/naco.2021057zbMath1485.90083OpenAlexW3217581017MaRDI QIDQ2074636
Xiaolei Fang, Fengming Lin, Zheming Gao
Publication date: 10 February 2022
Published in: Numerical Algebra, Control and Optimization (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.3934/naco.2021057
machine learningoperations researchdistributionally robust optimizationtractable methodsuncertain decision-making
Applications of mathematical programming (90C90) Minimax problems in mathematical programming (90C47) Research exposition (monographs, survey articles) pertaining to operations research and mathematical programming (90-02) Robustness in mathematical programming (90C17)
Related Items
CVaR-based optimization of environmental flow via the Markov lift of a mixed moving average process ⋮ Distributionally robust optimization by probability criterion for estimating a bounded signal ⋮ Distributional robustness and lateral transshipment for disaster relief logistics planning under demand ambiguity ⋮ Polyhedral coherent risk measure and distributionally robust portfolio optimization ⋮ A multivariate Chebyshev bound of the Selberg form
Uses Software
Cites Work
- Ambiguous Chance-Constrained Binary Programs under Mean-Covariance Information
- Minimax analysis of stochastic problems
- The minimax approach to stochastic programming and an illustrative application
- Maximum entropy and the moment problem
- Technical Note—A Duality Theory for Convex Programming with Set-Inclusive Constraints
- 10.1162/153244303321897726
- Stochastic Optimization: A Review
- On Choosing and Bounding Probability Metrics
- Generalized Chebychev Inequalities: Theory and Applications in Decision Analysis
- Semidefinite Programming
- A scenario aggregation algorithm for the solution of stochastic dynamic minimax problems
- The Monge-Kantorovich problem: achievements, connections, and perspectives
- Conic Programming Reformulations of Two-Stage Distributionally Robust Linear Programs over Wasserstein Balls
- Risk-Averse Two-Stage Stochastic Program with Distributional Ambiguity
- Sample Out-of-Sample Inference Based on Wasserstein Distance
- The Distributionally Robust Chance-Constrained Vehicle Routing Problem
- Robust Markov Decision Processes
- Regularization via Mass Transportation
- Chebyshev Inequalities for Products of Random Variables
- Robust Wasserstein profile inference and applications to machine learning
- A Cutting Surface Algorithm for Semi-Infinite Convex Programming with an Application to Moment Robust Optimization
- Robust Regression and Lasso
- Newsvendor optimization with limited distribution information
- Optimal Inequalities in Probability Theory: A Convex Optimization Approach
- Variance-based regularization with convex objectives
- Sublinear optimization for machine learning
- Convex Approximations of Chance Constrained Programs
- A Semidefinite Programming Approach to Optimal-Moment Bounds for Convex Classes of Distributions
- Distributionally Robust Reward-Risk Ratio Optimization with Moment Constraints
- Cooperative Data-Driven Distributionally Robust Optimization
- Lectures on Choquet's theorem
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Generalized Gauss inequalities via semidefinite programming
- Optimality conditions for semi-infinite and generalized semi-infinite programs via lower order exact penalty functions
- Data-driven chance constrained stochastic program
- A new exact penalty method for semi-infinite programming problems
- Models and algorithms for distributionally robust least squares problems
- Solving semi-infinite programs by smoothing projected gradient method
- Distributionally robust multi-item newsvendor problems with multimodal demand distributions
- On the rate of convergence in Wasserstein distance of the empirical measure
- On reduced semidefinite programs for second order moment bounds with applications
- Moment inequalities for sums of random matrices and their applications in optimization
- Characterization of the equivalence of robustification and regularization in linear and matrix regression
- Learning models with uniform performance via distributionally robust optimization
- Quantitative concentration inequalities for empirical measures on non-compact spaces
- Stochastic 0-1 linear programming under limited distributional information
- Measure theory and probability theory.
- Robust optimization - a comprehensive survey
- Robust solutions of uncertain linear programs
- Second-order cone programming
- Robust solutions of linear programming problems contaminated with uncertain data
- Distributionally robust optimization with matrix moment constraints: Lagrange duality and cutting plane methods
- Recent developments on the moment problem
- Data-driven robust optimization
- Distributionally robust expectation inequalities for structured distributions
- Identifying effective scenarios in distributionally robust stochastic programs with total variation distance
- Applying the minimax criterion in stochastic recourse programs
- Data-driven distributionally robust optimization using the Wasserstein metric: performance guarantees and tractable reformulations
- Robust sample average approximation
- Likelihood robust optimization for data-driven problems
- Exact algorithms for the chance-constrained vehicle routing problem
- Central limit theorems for the Wasserstein distance between the empirical and the true distributions
- The earth mover's distance as a metric for image retrieval
- Algorithms for the solution of stochastic dynamic minimax problems
- Distributionally robust joint chance constraints with second-order moment information
- Portfolio selection under model uncertainty: a penalized moment-based optimization approach
- Distributionally robust SDDP
- Tutorial on risk neutral, distributionally robust and risk averse multistage stochastic programming
- Recent advances in robust optimization: an overview
- A distributionally robust optimization approach for outpatient colonoscopy scheduling
- Wasserstein distributionally robust shortest path problem
- A distributionally robust perspective on uncertainty quantification and chance constrained programming
- On distributionally robust chance-constrained linear programs
- Stochastic dual dynamic integer programming
- Closed-form optimal portfolios of distributionally robust mean-CVaR problems with unknown mean and variance
- Decomposition algorithm for distributionally robust optimization using Wasserstein metric with an application to a class of regression models
- Tractable approximations to robust conic optimization problems
- Ambiguous chance constrained problems and robust optimization
- Worst-case distribution analysis of stochastic programs
- On sharpness of Tchebycheff-type inequalities
- On mass transportation
- Statistical decision functions which minimize the maximum risk
- Robust Convex Optimization
- Robustness to Dependency in Portfolio Optimization Using Overlapping Marginals
- Convergence Analysis for Distributionally Robust Optimization and Equilibrium Problems
- Computationally Tractable Counterparts of Distributionally Robust Constraints on Risk Measures
- A Distributional Interpretation of Robust Optimization
- Distributionally Robust Stochastic Knapsack Problem
- Robustifying Convex Risk Measures for Linear Portfolios: A Nonparametric Approach
- Distributionally Robust Convex Optimization
- Introduction to Stochastic Programming
- Distributionally Robust Optimization Under Moment Uncertainty with Application to Data-Driven Problems
- Distributionally Robust Optimization and Its Tractable Approximations
- Uncertainties in minimax stochastic programs
- Theory and Applications of Robust Optimization
- Semi-Infinite Programming: Theory, Methods, and Applications
- TRACTABLE ROBUST EXPECTED UTILITY AND RISK MODELS FOR PORTFOLIO OPTIMIZATION
- Lipschitz Behavior of the Robust Regularization
- Models for Minimax Stochastic Linear Optimization Problems with Risk Aversion
- Expected Value of Distribution Information for the Newsvendor Problem
- Robust Mean-Covariance Solutions for Stochastic Optimization
- Generalized Chebyshev Bounds via Semidefinite Programming
- Oracle-Based Robust Optimization via Online Learning
- Feasible Method for Semi-Infinite Programs
- Ambiguous Risk Measures and Optimal Robust Portfolios
- Semi-infinite programming, duality, discretization and optimality conditions†
- Linear Programming
- Worst-Case Value-At-Risk and Robust Portfolio Optimization: A Conic Programming Approach
- The Price of Robustness
- Robust Stochastic Approximation Approach to Stochastic Programming
- An exact penalty function for semi-infinite programming
- The Distribution Free Newsboy Problem: Review and Extensions
- Robust Solutions to Least-Squares Problems with Uncertain Data
- Distributionally Robust Optimization with Principal Component Analysis
- Distributionally Robust Stochastic Programming
- Probability approximation schemes for stochastic programs with distributionally robust second-order dominance constraints
- Approximations for Probability Distributions and Stochastic Optimization Problems
- Data-driven robust mean-CVaR portfolio selection under distribution ambiguity
- On a Class of Minimax Stochastic Programs