Convergence analysis of sample average approximation of two-stage stochastic generalized equations

Xiaojun Chen, Alexander Shapiro, Hailin Sun

Research output: Journal article publicationJournal articleAcademic researchpeer-review

18 Citations (Scopus)

Abstract

A solution of two-stage stochastic generalized equations is a pair: a first stage solution which is independent of realization of the random data and a second stage solution which is a function of random variables. This paper studies convergence of the sample average approximation of two-stage stochastic nonlinear generalized equations. In particular, an exponential rate of the convergence is shown by using the perturbed partial linearization of functions. Moreover, sufficient conditions for the existence, uniqueness, continuity, and regularity of solutions of two-stage stochastic generalized equations are presented under an assumption of monotonicity of the involved functions. These theoretical results are given without assuming relatively complete recourse and are illustrated by two-stage stochastic noncooperative games of two players.

Original languageEnglish
Pages (from-to)135-161
Number of pages27
JournalSIAM Journal on Optimization
Volume29
Issue number1
DOIs
Publication statusPublished - 17 Jan 2019

Keywords

  • Convergence
  • Exponential rate
  • Monotone multifunctions
  • Sample average approximation
  • Two-stage stochastic generalized equations

ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science

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