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 varieties 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 constrai...
| Main Authors: | , , , |
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| Format: | Journal Article |
| Published: |
Institute for Operations Research and the Management Sciences (I N F O R M S)
2010
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| Online Access: | http://hdl.handle.net/20.500.11937/11995 |
| Summary: | We review and develop different tractable approximations to individual chance constrained problems in robust optimization on a varieties 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 problem 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. |
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