Finite convergence of algorithms for nonlinear programs and variational inequalities
Journal of Optimization Theory and Applications
Mathematical Programming: Series A and B
A globally convergent Newton method for solving strongly monotone variational inequalities
Mathematical Programming: Series A and B
Weak sharp minima in mathematical programming
SIAM Journal on Control and Optimization
A general descent framework for the monotone variational inequality problem
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
On stationary points of the implicit Lagrangian for nonlinear complementarity problems
Journal of Optimization Theory and Applications
Unconstrained optimization reformulations of variational inequality problems
Journal of Optimization Theory and Applications
QPCOMP: a quadratic programming based solver for mixed complementarity problems
Mathematical Programming: Series A and B - Special issue on computational nonsmooth optimization
Equivalence of variational inequality problems to unconstrained minimization
Mathematical Programming: Series A and B
New NCP-functions and their properties
Journal of Optimization Theory and Applications
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
Weak Sharp Solutions of Variational Inequalities
SIAM Journal on Optimization
A Linearly Convergent Derivative-Free Descent Method for Strongly Monotone Complementarity Problems
Computational Optimization and Applications
Operations Research Letters
Some recent advances in projection-type methods for variational inequalities
Journal of Computational and Applied Mathematics - Proceedings of the international conference on recent advances in computational mathematics
Hi-index | 0.00 |
The D-gap function has been useful in developing unconstrained descent methods for solving strongly monotone variational inequality problems. We show that the D-gap function has certain properties that are useful also for monotone variational inequality problems with bounded feasible set. Accordingly, we develop two unconstrained methods based on them that are similar in spirit to a feasible method of Zhu and Marcotte based on the regularized-gap function. We further discuss a third method based on applying the D-gap function to a regularized problem. Preliminary numerical experience is also reported.