Please use this identifier to cite or link to this item: https://doi.org/10.1287/opre.1090.0712
Title: From CVaR to uncertainty set: Implications in joint chance-constrained optimization
Authors: Chen, W.
Sim, M. 
Sun, J. 
Teo, C.-P. 
Keywords: Decision analysis: risk
Nonlinear
Probability: application
Programming: stochastic
Issue Date: 2010
Source: Chen, W., Sim, M., Sun, J., Teo, C.-P. (2010). From CVaR to uncertainty set: Implications in joint chance-constrained optimization. Operations Research 58 (2) : 470-485. ScholarBank@NUS Repository. https://doi.org/10.1287/opre.1090.0712
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. ©2010 INFORMS.
Source Title: Operations Research
URI: http://scholarbank.nus.edu.sg/handle/10635/44178
ISSN: 0030364X
DOI: 10.1287/opre.1090.0712
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