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dc.contributor.authorRockafellar, R.
dc.contributor.authorSun, Jie
dc.date.accessioned2018-06-29T12:27:06Z
dc.date.available2018-06-29T12:27:06Z
dc.date.created2018-06-29T12:08:48Z
dc.date.issued2018
dc.identifier.citationRockafellar, R. and Sun, J. 2018. Solving monotone stochastic variational inequalities and complementarity problems by progressive hedging. Mathematical Programming. 174 (1-2): pp. 453-471.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/68777
dc.identifier.doi10.1007/s10107-018-1251-y
dc.description.abstract

The concept of a stochastic variational inequality has recently been articulated in a new way that is able to cover, in particular, the optimality conditions for a multistage stochastic programming problem. One of the long-standing methods for solving such an optimization problem under convexity is the progressive hedging algorithm. That approach is demonstrated here to be applicable also to solving multistage stochastic variational inequality problems under monotonicity, thus increasing the range of applications for progressive hedging. Stochastic complementarity problems as a special case are explored numerically in a linear two-stage formulation.

dc.publisherSpringer
dc.titleSolving monotone stochastic variational inequalities and complementarity problems by progressive hedging
dc.typeJournal Article
dcterms.source.startPage1
dcterms.source.endPage19
dcterms.source.issn0025-5610
dcterms.source.titleMathematical Programming
curtin.note

The final publication is available at Springer via http://dx.doi.org/10.1007/s10107-018-1251-y

curtin.departmentSchool of Electrical Engineering, Computing and Mathematical Science (EECMS)
curtin.accessStatusOpen access


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