Title
From CVaR to Uncertainty Set: Implications in Joint Chance-Constrained Optimization
Abstract
We review and develop different tractable approximations to individual chance-constrained problems in robust optimization on a variety of uncertainty sets and show their interesting connections with bounds on the conditional-value-at-risk (CVaR) measure. We extend the idea to joint chance-constrained problems and provide a new formulation that improves upon the standard approach. Our approach builds on a classical worst-case bound for order statistics problems and is applicable even if the constraints are correlated. We provide an application of the model on a network resource allocation problem with uncertain demand.
Year
DOI
Venue
2010
10.1287/opre.1090.0712
Operations Research
Keywords
Field
DocType
individual chance-constrained problem,joint chance-constrained optimization,new formulation,uncertainty set,different tractable approximation,standard approach,uncertain demand,joint chance-constrained problem,robust optimization,order statistics problem,interesting connection,network resource allocation problem,order statistic,stochastic,conditional value at risk,risk,resource allocation,application,decision analysis,nonlinear,probability,programming,constrained optimization
Mathematical optimization,Robust optimization,Nonlinear programming,Resource allocation,Risk management,Order statistic,Stochastic programming,Mathematics,Operations management,CVAR,Constrained optimization
Journal
Volume
Issue
ISSN
58
2
0030-364X
Citations 
PageRank 
References 
71
2.45
19
Authors
4
Name
Order
Citations
PageRank
Wenqing Chen1893.90
Melvyn Sim21909117.68
Jie Sun31303113.30
Chung-Piaw Teo486469.27