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    Solving monotone stochastic variational inequalities and complementarity problems by progressive hedging

    266794.pdf (309.8Kb)
    Access Status
    Open access
    Authors
    Rockafellar, R.
    Sun, Jie
    Date
    2018
    Type
    Journal Article
    
    Metadata
    Show full item record
    Citation
    Rockafellar, R. and Sun, J. 2018. Solving monotone stochastic variational inequalities and complementarity problems by progressive hedging. Mathematical Programming. 174 (1-2): pp. 453-471.
    Source Title
    Mathematical Programming
    DOI
    10.1007/s10107-018-1251-y
    ISSN
    0025-5610
    School
    School of Electrical Engineering, Computing and Mathematical Science (EECMS)
    Remarks

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

    URI
    http://hdl.handle.net/20.500.11937/68777
    Collection
    • Curtin Research Publications
    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.

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