From CVaR to Uncertainty Set: Implications in Joint Chance-Constrained Optimization

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-constraine...

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Veröffentlicht in:Operations research 2010-03, Vol.58 (2), p.470-485
Hauptverfasser: Chen, Wenqing, Sim, Melvyn, Sun, Jie, Teo, Chung-Piaw
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Sprache:eng
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Zusammenfassung: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.
ISSN:0030-364X
1526-5463
DOI:10.1287/opre.1090.0712