On the unconstrained optimization reformulations for a class of stochastic vector variational inequality problems

On the unconstrained optimization reformulations for a class of stochastic vector variational inequality problems

Abstract In this paper, a class of stochastic vector variational inequality (SVVI) problems are considered. By employing the idea of a D-gap function, the SVVI problem is reformulated as a deterministic model, which is an unconstrained expected residual minimization (UERM) problem, while it is refor...

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Bibliographic Details
Main Authors: Dan-dan Dong, Guo-ji Tang, Hui-ming Qiu
Format: Article
Language:English
Published: SpringerOpen 2023-07-01
Series:Journal of Inequalities and Applications
Subjects:
Stochastic vector variational inequality
D-gap function
Sample average approximation
Convergence
Error bound
Online Access:https://doi.org/10.1186/s13660-023-03011-2

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