A data-driven distributionally robust bound on the expected optimal value of uncertain mixed 0-1 linear programming
From MaRDI portal
Publication:1789641
DOI10.1007/s10287-018-0298-9zbMath1397.90272arXiv1708.07603OpenAlexW2746085324MaRDI QIDQ1789641
Publication date: 10 October 2018
Published in: Computational Management Science (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1708.07603
Wasserstein metricsemidefinite programmingcopositive programmingdistributionally robust optimization
Semidefinite programming (90C22) Approximation methods and heuristics in mathematical programming (90C59) Boolean programming (90C09)
Related Items
Frameworks and results in distributionally robust optimization, Exploiting partial correlations in distributionally robust optimization
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Data-driven chance constrained stochastic program
- Representing quadratically constrained quadratic programs as generalized copositive programs
- Distributionally robust multi-item newsvendor problems with multimodal demand distributions
- On reduced semidefinite programs for second order moment bounds with applications
- Semidefinite programming versus the reformulation-linearization technique for nonconvex quadratically constrained quadratic programming
- The ellipsoid method and its consequences in combinatorial optimization
- Data-driven robust optimization
- Data-driven distributionally robust optimization using the Wasserstein metric: performance guarantees and tractable reformulations
- The earth mover's distance as a metric for image retrieval
- Distributionally robust joint chance constraints with second-order moment information
- A gentle, geometric introduction to copositive optimization
- On distributionally robust chance-constrained linear programs
- On the copositive representation of binary and continuous nonconvex quadratic programs
- Ambiguous chance constrained problems and robust optimization
- Persistence in discrete optimization under data uncertainty
- The ?(2) limit in the random assignment problem
- Copositive Programming
- Distributionally Robust Convex Optimization
- Distributionally Robust Optimization Under Moment Uncertainty with Application to Data-Driven Problems
- Mixed 0-1 Linear Programs Under Objective Uncertainty: A Completely Positive Representation
- Persistency Model and Its Applications in Choice Modeling
- Generalized Chebyshev Bounds via Semidefinite Programming
- Worst-Case Value-At-Risk and Robust Portfolio Optimization: A Conic Programming Approach
- Bounding the Project Completion Time Distribution in PERT Networks
- Ambiguous Joint Chance Constraints Under Mean and Dispersion Information
- Probabilistic Combinatorial Optimization: Moments, Semidefinite Programming, and Asymptotic Bounds
- The minimax approach to stochastic programming and an illustrative application
- Efficient Estimation of Arc Criticalities in Stochastic Activity Networks
- Optimal Inequalities in Probability Theory: A Convex Optimization Approach
- Ambiguity in portfolio selection
- On Cones of Nonnegative Quadratic Functions
