Projected gradient methods for linearly constrained problems
Mathematical Programming: Series A and B
Practical methods of optimization; (2nd ed.)
Practical methods of optimization; (2nd ed.)
USSR Computational Mathematics and Mathematical Physics
A globally convergent Newton method for solving strongly monotone variational inequalities
Mathematical Programming: Series A and B
Improvements of some projection methods for monotone nonlinear variational inequalities
Journal of Optimization Theory and Applications
Journal of Optimization Theory and Applications
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
Interior projection-like methods for monotone variational inequalities
Mathematical Programming: Series A and B
A note on a globally convergent Newton method for solving monotone variational inequalities
Operations Research Letters
| Hi-index | 7.29 |
In this paper, we proposed a modified extragradient method for solving variational inequalities. The method can be viewed as an extension of the method proposed by He and Liao [Improvement of some projection methods for monotone variational inequalities, J. Optim. Theory Appl. 112 (2002) 111-128], by performing an additional projection step at each iteration and another optimal step length is employed to reach substantial progress in each iteration. We used a self-adaptive technique to adjust parameter @r at each iteration. Under certain conditions, the global convergence of the proposed method is proved. Preliminary numerical experiments are included to compare our method with some known methods.