A Projection-Based Algorithm for Solving Stochastic Inverse Variational Inequality Problems

Zeinab Alizadeh, Felipe Parra Polanco, Afrooz Jalilzadeh

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We consider a stochastic Inverse Variational Inequality (IVI) problem defined by a continuous and cocoercive map over a closed and convex set. Motivated by the absence of performance guarantees for stochastic IVI, we present a variance-reduced projection-based gradient method. Our proposed method ensures an almost sure convergence of the generated iterates to the solution, and we establish a convergence rate guarantee. To verify our results, we apply the proposed algorithm to a network equilibrium control problem.

Original languageEnglish (US)
Title of host publication2023 Winter Simulation Conference, WSC 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3532-3540
Number of pages9
ISBN (Electronic)9798350369663
DOIs
StatePublished - 2023
Event2023 Winter Simulation Conference, WSC 2023 - San Antonio, United States
Duration: Dec 10 2023Dec 13 2023

Publication series

NameProceedings - Winter Simulation Conference
ISSN (Print)0891-7736

Conference

Conference2023 Winter Simulation Conference, WSC 2023
Country/TerritoryUnited States
CitySan Antonio
Period12/10/2312/13/23

ASJC Scopus subject areas

  • Software
  • Modeling and Simulation
  • Computer Science Applications

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