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dc.contributor.authorChen, W.
dc.contributor.authorSim, M.
dc.contributor.authorSun, Jie
dc.contributor.authorteo, C.
dc.date.accessioned2017-01-30T11:28:05Z
dc.date.available2017-01-30T11:28:05Z
dc.date.created2014-09-02T20:01:17Z
dc.date.issued2010
dc.identifier.citationChen, W. and Sim, M. and Sun, J. and teo, C. 2010. From CVaR to Uncertainty Set: Implications in Joint Chance-Constrained Optimization. Operations Research. 58: pp. 470-485.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/11995
dc.identifier.doi10.1287/opre.1090.0712
dc.description.abstract

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.

dc.publisherInstitute for Operations Research and the Management Sciences (I N F O R M S)
dc.titleFrom CVaR to Uncertainty Set: Implications in Joint Chance-Constrained Optimization
dc.typeJournal Article
dcterms.source.volume58
dcterms.source.startPage470
dcterms.source.endPage485
dcterms.source.issn0030-364X
dcterms.source.titleOperations Research
curtin.accessStatusFulltext not available


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