## Journals

- Advances in Mathematics of Communications
- Big Data & Information Analytics
- Communications on Pure & Applied Analysis
- Discrete & Continuous Dynamical Systems - A
- Discrete & Continuous Dynamical Systems - B
- Discrete & Continuous Dynamical Systems - S
- Evolution Equations & Control Theory
- Foundations of Data Science
- Inverse Problems & Imaging
- Journal of Computational Dynamics
- Journal of Dynamics & Games
- Journal of Geometric Mechanics
- Journal of Industrial & Management Optimization
- Journal of Modern Dynamics
- Kinetic & Related Models
- Mathematical Biosciences & Engineering
- Mathematical Control & Related Fields
- Mathematical Foundations of Computing
- Networks & Heterogeneous Media
- Numerical Algebra, Control & Optimization
- AIMS Mathematics
- Conference Publications
- Electronic Research Announcements
- Mathematics in Engineering

### Open Access Journals

NACO

In this paper, we study the
stochastic variational inequality problem (SVIP)
from a viewpoint of minimization of conditional value-at-risk. We employ the D-gap residual function for VIPs to define
a loss function for SVIPs. In order to reduce the risk of high losses in applications of SVIPs, we use the
D-gap function and conditional value-at-risk to present a deterministic
minimization reformulation for SVIPs. We show that the new
reformulation is a convex program under suitable conditions.
Furthermore, by using the smoothing techniques and the Monte Carlo
methods, we propose a smoothing approximation method for finding a
solution of the new reformulation and show that this method is
globally convergent with probability one.

JIMO

We consider a class of stochastic nonlinear complementarity
problems. We propose a new reformulation of the stochastic
complementarity problem, that is, a two-stage stochastic
mathematical programming model reformulation. Based on this
reformulation, we propose a smoothing-based sample average
approximation method for stochastic complementarity problem and
prove its convergence. As an application, a supply chain
super-network equilibrium is modeled as a stochastic nonlinear
complementarity problem and numerical results on the problem are
reported.

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