A study of data-driven distributionally robust optimization with incomplete joint data under finite support
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Publication:2098046
DOI10.1016/j.ejor.2022.06.032OpenAlexW4283163227MaRDI QIDQ2098046
Publication date: 17 November 2022
Published in: European Journal of Operational Research (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.ejor.2022.06.032
stochastic programmingmissing datauncertainty modelingdistributionally robust optimizationdata-driven decision-making
Uses Software
Cites Work
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- Data-driven chance constrained stochastic program
- Scenario construction and reduction applied to stochastic power generation expansion planning
- A simulation-based approach to two-stage stochastic programming with recourse
- Maximum likelihood estimation for incomplete multinomial data via the weaver algorithm
- EM algorithm in Gaussian copula with missing data
- Data-driven robust optimization
- 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
- Scenario reduction revisited: fundamental limits and guarantees
- Data-driven risk-averse stochastic optimization with Wasserstein metric
- A practical inventory control policy using operational statistics
- Ambiguous chance constrained problems and robust optimization
- The Sample Average Approximation Method for Stochastic Discrete Optimization
- Distributionally Robust Convex Optimization
- Distributionally Robust Optimization Under Moment Uncertainty with Application to Data-Driven Problems
- Integer Programming
- Divergence measures based on the Shannon entropy
- Robust Stochastic Approximation Approach to Stochastic Programming
- Inference and missing data
- Assessing the accuracy of the maximum likelihood estimator: Observed versus expected Fisher information
- Asymptotic Statistics
- Statistical Analysis with Missing Data, Third Edition
- A two-stage stochastic programming framework for transportation planning in disaster response
- Conic Programming Reformulations of Two-Stage Distributionally Robust Linear Programs over Wasserstein Balls
- Risk-Averse Two-Stage Stochastic Program with Distributional Ambiguity
- Distributionally Robust Optimization with Infinitely Constrained Ambiguity Sets
- Variational Theory for Optimization under Stochastic Ambiguity
- Ambiguity in portfolio selection
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