A New Projection Algorithm for Generalized Variational Inequality

A New Projection Algorithm for Generalized Variational Inequality

A New Projection Method for Variational Inequality Problems∗

We propose a new projection algorithm for solving the variational inequality problem, where the underlying function is continuous and satisfies a certain generalized monotonicity assumption (e.g., it can be pseudomonotone). The method is simple and admits a nice geometric interpretation. It consists of two steps. First, we construct an appropriate hyperplane which strictly separates the current...

A new type algorithm for the generalized variational inequality with multi-valued mapping

In this paper, the generalized variational inequality with multi-valued mapping (GVI) is considered. To solve the problem, we first establish a global error bound estimation for GVI with the underlying multi-valued mapping being   strict monotone and Holder continuous. Based on this, we propose a new type of method to solve the GVI, and its global convergence is also established. Keywords-GVI...

A New Algorithm for Stochastic Variational Inequality with an Application

Recently stochastic variational inequality has been extensively studied. However there are few methods can be effectively realized. This study considers to solve stochastic variational inequality by combining quasi-Monte Carlo approach and interior point method. The global convergence is established for the new algorithm. An application for the synergies analysis of the supply chain after M&A f...

New Double Projection Algorithm for Solving Variational Inequalities

We propose a class of new double projection algorithms for solving variational inequality problem, which can be viewed as a framework of the method of Solodov and Svaiter by adopting a class of new hyperplanes. By the separation property of hyperplane, our method is proved to be globally convergent under very mild assumptions. In addition, we propose a modified version of our algorithm that fin...