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Convergence analysis of sample average approximation for a class of stochastic nonlinear complementarity problems: from two-stage to multistage

In this paper, we consider the sample average approximation (SAA) approach for a class of stochastic nonlinear complementarity problems (SNCPs) and study the corresponding convergence properties. We first investigate the convergence of the SAA counterparts of two-stage SNCPs when the first-stage pro...

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Autores principales: Jiang, Jie, Sun, Hailin, Zhou, Bin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8076443/
https://www.ncbi.nlm.nih.gov/pubmed/33935468
http://dx.doi.org/10.1007/s11075-021-01110-z
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author Jiang, Jie
Sun, Hailin
Zhou, Bin
author_facet Jiang, Jie
Sun, Hailin
Zhou, Bin
author_sort Jiang, Jie
collection PubMed
description In this paper, we consider the sample average approximation (SAA) approach for a class of stochastic nonlinear complementarity problems (SNCPs) and study the corresponding convergence properties. We first investigate the convergence of the SAA counterparts of two-stage SNCPs when the first-stage problem is continuously differentiable and the second-stage problem is locally Lipschitz continuous. After that, we extend the convergence results to a class of multistage SNCPs whose decision variable of each stage is influenced only by the decision variables of adjacent stages. Finally, some preliminary numerical tests are presented to illustrate the convergence results.
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spelling pubmed-80764432021-04-27 Convergence analysis of sample average approximation for a class of stochastic nonlinear complementarity problems: from two-stage to multistage Jiang, Jie Sun, Hailin Zhou, Bin Numer Algorithms Original Paper In this paper, we consider the sample average approximation (SAA) approach for a class of stochastic nonlinear complementarity problems (SNCPs) and study the corresponding convergence properties. We first investigate the convergence of the SAA counterparts of two-stage SNCPs when the first-stage problem is continuously differentiable and the second-stage problem is locally Lipschitz continuous. After that, we extend the convergence results to a class of multistage SNCPs whose decision variable of each stage is influenced only by the decision variables of adjacent stages. Finally, some preliminary numerical tests are presented to illustrate the convergence results. Springer US 2021-04-27 2022 /pmc/articles/PMC8076443/ /pubmed/33935468 http://dx.doi.org/10.1007/s11075-021-01110-z Text en © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2021 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Original Paper
Jiang, Jie
Sun, Hailin
Zhou, Bin
Convergence analysis of sample average approximation for a class of stochastic nonlinear complementarity problems: from two-stage to multistage
title Convergence analysis of sample average approximation for a class of stochastic nonlinear complementarity problems: from two-stage to multistage
title_full Convergence analysis of sample average approximation for a class of stochastic nonlinear complementarity problems: from two-stage to multistage
title_fullStr Convergence analysis of sample average approximation for a class of stochastic nonlinear complementarity problems: from two-stage to multistage
title_full_unstemmed Convergence analysis of sample average approximation for a class of stochastic nonlinear complementarity problems: from two-stage to multistage
title_short Convergence analysis of sample average approximation for a class of stochastic nonlinear complementarity problems: from two-stage to multistage
title_sort convergence analysis of sample average approximation for a class of stochastic nonlinear complementarity problems: from two-stage to multistage
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8076443/
https://www.ncbi.nlm.nih.gov/pubmed/33935468
http://dx.doi.org/10.1007/s11075-021-01110-z
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AT zhoubin convergenceanalysisofsampleaverageapproximationforaclassofstochasticnonlinearcomplementarityproblemsfromtwostagetomultistage