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 D-gap function, SVVI problem is reformulated as deterministic model, which an unconstrained expected residual minimization (UERM) problem, while it constrained in work Zhao et al. Then, properties objective function investigated and sample average approximation approach proposed for solving UERM problem. Convergence global optimal solutions stationary points analyzed. Moreover, we consider another formulation, i.e., value (EV) formulation error bound based on EV given.