Solving monotone stochastic variational inequalities and complementarity problems by progressive hedging

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...

Full description

Bibliographic Details
Main Authors: Rockafellar, R., Sun, Jie
Format: Journal Article
Published: Springer 2018
Online Access:http://hdl.handle.net/20.500.11937/68777
_version_ 1848761887350587392
author Rockafellar, R.
Sun, Jie
author_facet Rockafellar, R.
Sun, Jie
author_sort Rockafellar, R.
building Curtin Institutional Repository
collection Online Access
description 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.
first_indexed 2025-11-14T10:38:49Z
format Journal Article
id curtin-20.500.11937-68777
institution Curtin University Malaysia
institution_category Local University
last_indexed 2025-11-14T10:38:49Z
publishDate 2018
publisher Springer
recordtype eprints
repository_type Digital Repository
spelling curtin-20.500.11937-687772019-04-15T03:51:39Z Solving monotone stochastic variational inequalities and complementarity problems by progressive hedging Rockafellar, R. Sun, Jie 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. 2018 Journal Article http://hdl.handle.net/20.500.11937/68777 10.1007/s10107-018-1251-y Springer fulltext
spellingShingle Rockafellar, R.
Sun, Jie
Solving monotone stochastic variational inequalities and complementarity problems by progressive hedging
title Solving monotone stochastic variational inequalities and complementarity problems by progressive hedging
title_full Solving monotone stochastic variational inequalities and complementarity problems by progressive hedging
title_fullStr Solving monotone stochastic variational inequalities and complementarity problems by progressive hedging
title_full_unstemmed Solving monotone stochastic variational inequalities and complementarity problems by progressive hedging
title_short Solving monotone stochastic variational inequalities and complementarity problems by progressive hedging
title_sort solving monotone stochastic variational inequalities and complementarity problems by progressive hedging
url http://hdl.handle.net/20.500.11937/68777