Discrete Approximation and Quantification in Distributionally Robust Optimization

DOI10.1287/moor.2017.0911zbMath1440.90041OpenAlexW2891033779WikidataQ129236450 ScholiaQ129236450MaRDI QIDQ5219706

Huifu Xu, Alois Pichler, Yong-Chao Liu

Publication date: 12 March 2020

Published in: Mathematics of Operations Research (Search for Journal in Brave)

Full work available at URL: https://eprints.soton.ac.uk/414753/1/LPX_MOR_17_final.pdf

zbMATH Keywords

moment conditionsnested distanceHoffman's lemmadiscretization of ambiguity setKantorovich/Wasserstein metric

Mathematics Subject Classification ID

Minimax problems in mathematical programming (90C47) Sensitivity, stability, parametric optimization (90C31) Stochastic programming (90C15) Robustness in mathematical programming (90C17)

Related Items (6)

Stability of a class of risk-averse multistage stochastic programs and their distributionally robust counterparts ⋮ Decision bounding problems for two-stage distributionally robust stochastic bilevel optimization ⋮ Pure characteristics demand models and distributionally robust mathematical programs with stochastic complementarity constraints ⋮ On distributionally robust optimization problems with \(k\)-th order stochastic dominance constraints induced by full random quadratic recourse ⋮ Twisted probabilities, uncertainty, and prices ⋮ Quantitative stability analysis for minimax distributionally robust risk optimization

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