Robust Stochastic Optimization With Convex Risk Measures: A Discretized Subgradient Scheme

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Robust Stochastic Optimization With Convex Risk Measures: A Discretized Subgradient Scheme

We study the distributionally robust stochastic optimization problem within a general framework of risk measures, in which the ambiguity set is described by a spectrum of practically used probability distribution constraints such as bounds on mean-deviation and entropic value-at-risk. We show that a...

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Bibliographic Details
Main Authors:	Yu, H., Sun, Jie
Format:	Journal Article
Language:	English
Published:	AMER INST MATHEMATICAL SCIENCES-AIMS 2021
Subjects:	Science & Technology Technology Physical Sciences Engineering, Multidisciplinary Operations Research & Management Science Mathematics, Interdisciplinary Applications Engineering Mathematics Stochastic optimization distributionally robust convex risk measure subgradient method two-stage optimization problem LINEAR OPTIMIZATION PROGRAMS MODELS
Online Access:	http://purl.org/au-research/grants/arc/DP160102819 http://hdl.handle.net/20.500.11937/90790

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