Parallel and distributed computation: numerical methods
Parallel and distributed computation: numerical methods
Mathematical Programming: Series A and B
A class of gap functions for variational inequalities
Mathematical Programming: Series A and B
Nonlinear complementarity as unconstrained and constrained minimization
Mathematical Programming: Series A and B - Special issue: Festschrift in Honor of Philip Wolfe part II: studies in nonlinear programming
Unconstrained optimization reformulations of variational inequality problems
Journal of Optimization Theory and Applications
Equivalent Unconstrained Minimization and Global Error Bounds for Variational Inequality Problems
SIAM Journal on Control and Optimization
Equivalence of variational inequality problems to unconstrained minimization
Mathematical Programming: Series A and B
Error bounds in mathematical programming
Mathematical Programming: Series A and B - Special issue: papers from ismp97, the 16th international symposium on mathematical programming, Lausanne EPFL
Mathematical Programming: Series A and B
Global projection-type error bounds for general variational inequalities
Journal of Optimization Theory and Applications
Error Bounds of Regularized Gap Functions for Nonsmooth Variational Inequality Problems
Mathematical Programming: Series A and B
Global bounds for the distance to solutions of co-coercive variational inequalities
Operations Research Letters
A note on a globally convergent Newton method for solving monotone variational inequalities
Operations Research Letters
Hi-index | 7.29 |
The set-valued variational inequality problem is very useful in economics theory and nonsmooth optimization. In this paper, we introduce some gap functions for set-valued variational inequality problems under suitable assumptions. By using these gap functions we derive global error bounds for the solution of the set-valued variational inequality problems. Our results not only generalize the previously known results for classical variational inequalities from single-valued case to set-valued, but also present a way to construct gap functions and derive global error bounds for set-valued variational inequality problems.