\(\alpha \)-conservative approximation for probabilistically constrained convex programs

DOI10.1007/s10589-008-9178-5zbMath1189.90112OpenAlexW2073913588MaRDI QIDQ969716

Yuichi Takano, Jun-Ya Gotoh

Publication date: 7 May 2010

Published in: Computational Optimization and Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10589-008-9178-5

zbMATH Keywords

branch-and-boundD.C. optimizationchance constraintvalue-at-risk minimization

Mathematics Subject Classification ID

Convex programming (90C25) Stochastic programming (90C15)

Cites Work

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• Optimization on low rank nonconvex structures
• Robust solutions of linear programming problems contaminated with uncertain data
• Uncertain convex programs: randomized solutions and confidence levels
• A mixed integer linear programming formulation of the optimal mean/Value-at-Risk portfolio problem
• Coherent Measures of Risk
• Incorporating Asymmetric Distributional Information in Robust Value-at-Risk Optimization
• Worst-Case Value-At-Risk and Robust Portfolio Optimization: A Conic Programming Approach
• The Price of Robustness
• On the global minimization of the value-at-risk
• Chance Constrained Programming with Joint Constraints
• Convex Approximations of Chance Constrained Programs
• Convex analysis and global optimization

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