Data-driven robust chance constrained problems: a mixture model approach
type: Item
instance of: scholarly article
title: Data-driven robust chance constrained problems: a mixture model approach
zbMATH Open document ID: 1402.90104
author: Zhiping Chen
author: Shen Peng
author: Jia Liu
published in: Journal of Optimization Theory and Applications
publication date: 2018-11-27T00:00:00Z
Mathematics Subject Classification ID: 90C15
Mathematics Subject Classification ID: 90C25
zbMATH DE Number: 6985509
zbMATH Keywords: data-driven
zbMATH Keywords: mixture distribution
zbMATH Keywords: distributionally robust optimization
zbMATH Keywords: chance constrained problem
zbMATH Keywords: convex approximation
describes a project that uses: QRM
MaRDI profile type: Publication
full work available at URL: s10957-018-1376-4
OpenAlex ID: W2888717625
cites work: Chance-constrained programming
cites work: Chance Constrained Programming with Joint Constraints
cites work: Q5718662
cites work: Q3126752
cites work: Lectures on Stochastic Programming
cites work: Q5645216
cites work: Chance-Constrained Programming with Joint Constraints
cites work: An integer programming approach for linear programs with probabilistic constraints
cites work: Q5201292
cites work: Robust solutions of linear programming problems contaminated with uncertain data
cites work: Convex Approximations of Chance Constrained Programs
cites work: Distributionally robust joint chance constraints with second-order moment information
cites work: On distributionally robust chance-constrained linear programs
cites work: Ambiguous chance constrained problems and robust optimization
cites work: Ambiguous risk constraints with moment and unimodality information
cites work: Distributionally Robust Optimization Under Moment Uncertainty with Application to Data-Driven Problems
cites work: Distributionally Robust Stochastic Knapsack Problem
cites work: Ambiguous Joint Chance Constraints Under Mean and Dispersion Information
cites work: Data-driven robust optimization
cites work: Portfolio management with robustness in both prediction and decision: a mixture model based learning approach
cites work: Q5706744
cites work: Worst-Case Conditional Value-at-Risk with Application to Robust Portfolio Management
cites work: The topography of multivariate normal mixtures
cites work: Dynamics of Markets
cites work: Probabilistic methods for algorithmic discrete mathematics
cites work: Weak convergence and empirical processes. With applications to statistics
cites work: The Scenario Approach to Robust Control Design
cites work: Q3182207
cites work: Stochastic geometric optimization with joint probabilistic constraints
cites work: Variational Analysis
cites work: Finite solution of pure trade markets with Cobb-Douglas utilities
Wikidata QID: Q129398875
DOI: 10.1007/S10957-018-1376-4
description: scientific article; zbMATH DE number 6985509