An Inexact Variance-Reduced Method for Stochastic Quasi-Variational Inequality Problems with an Application In Healthcare

Zeinab Alizadeh, Brianna M. Otero, Afrooz Jalilzadeh

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

Abstract

This paper is focused on a stochastic quasi-variational inequality (SQVI) problem with a continuous and strongly-monotone mapping over a closed and convex set where the projection onto the constraint set may not be easy to compute. We present an inexact variance reduced stochastic scheme to solve SQVI problems and analyzed its convergence rate and oracle complexity. A linear rate of convergence is obtained by progressively increasing sample-size and approximating the projection operator. Moreover, we show how a competition among blood donation organizations can be modeled as an SQVI and we provide some preliminary simulation results to validate our findings.

Original languageEnglish (US)
Title of host publicationProceedings of the 2022 Winter Simulation Conference, WSC 2022
EditorsB. Feng, G. Pedrielli, Y. Peng, S. Shashaani, E. Song, C.G. Corlu, L.H. Lee, E.P. Chew, T. Roeder, P. Lendermann
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3099-3109
Number of pages11
ISBN (Electronic)9798350309713
DOIs
StatePublished - 2022
Event2022 Winter Simulation Conference, WSC 2022 - Guilin, China
Duration: Dec 11 2022Dec 14 2022

Publication series

NameProceedings - Winter Simulation Conference
Volume2022-December

Conference

Conference2022 Winter Simulation Conference, WSC 2022
Country/TerritoryChina
CityGuilin
Period12/11/2212/14/22

ASJC Scopus subject areas

  • Software
  • Modeling and Simulation
  • Computer Science Applications

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