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dc.contributor.authorGao, S.
dc.contributor.authorKong, L.
dc.contributor.authorSun, Jie
dc.date.accessioned2017-01-30T15:34:20Z
dc.date.available2017-01-30T15:34:20Z
dc.date.created2014-06-29T20:00:19Z
dc.date.issued2014
dc.identifier.citationGao, S. and Kong, L. and Sun, J. 2014. Robust two-stage stochastic linear programs with moment constraints. Optimization. 63 (6): pp. 829-837.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/47589
dc.identifier.doi10.1080/02331934.2014.906598
dc.description.abstract

We consider the two-stage stochastic linear programming model, in which the recourse function is a worst case expected value over a set of probabilistic distributions. These distributions share the same first- and second-order moments. By using duality of semi-infinite programming and assuming knowledge on extreme points of the dual polyhedron of the constraints, we show that a deterministic equivalence of the two-stage problem is a second-order cone optimization problem. Numerical examples are presented to show non-conservativeness and computational advantage of this approach.

dc.publisherTaylor & Francis Ltd.
dc.subjectstochastic programming
dc.subjectsecond-order cone optimization
dc.titleRobust two-stage stochastic linear programs with moment constraints
dc.typeJournal Article
dcterms.source.volume63
dcterms.source.number6
dcterms.source.startPage829
dcterms.source.endPage837
dcterms.source.issn0233-1934
dcterms.source.titleOptimization
curtin.note

This is an Author's Accepted Manuscript of an article published in Optimization: A Journal of Mathematical Programming and Operations Research (2014), copyright Taylor & Francis, available online at: <a href="http://www.tandfonline.com/10.1080/02331934.2014.906598">http://www.tandfonline.com/10.1080/02331934.2014.906598</a>

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curtin.accessStatusOpen access


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