A regularized sample average approximation method for stochastic mathematical programs with nonsmooth equality constraints


Meng, F. and Xu, Huifu (2006) A regularized sample average approximation method for stochastic mathematical programs with nonsmooth equality constraints. SIAM Journal on Optimization, 17, (3), 891-919. (doi:10.1137/050638242).

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Original Publication URL: http://dx.doi.org/10.1137/050638242

Description/Abstract

We investigate a class of two stage stochastic programs where the second stage problem is subject to nonsmooth equality constraints parameterized by the first stage variant and a random vector. We consider the case when the parametric equality constraints have more than one solution. A regularization method is proposed to deal with the multiple solution problem, and a sample average approximation method is proposed to solve the regularized problem. We then investigate the convergence of stationary points of the regularized sample average approximation programs as the sample size increases. The established results are applied to stochastic mathematical programs with $P_0$-variational inequality constraints. Preliminary numerical results are reported.

Item Type: Article
ISSNs: 1052-6234 (print)
Related URLs:
Subjects: Q Science > QA Mathematics
Divisions: University Structure - Pre August 2011 > School of Mathematics > Operational Research
Item ID: 79542
Date Deposited: 17 Mar 2010
Last Modified: 02 Mar 2012 13:13
Contributors: Meng, F. (Author)
Xu, Huifu (Author)
Date: 2006
Status: Published
URI: http://eprints.soton.ac.uk/id/eprint/79542

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