Inexact Newton methods for the nonlinear complementarity problem
Mathematical Programming: Series A and B
On the convergence of the proximal point algorithm for convex minimization
SIAM Journal on Control and Optimization
Approximate iterations in Bregman-function-based proximal algorithms
Mathematical Programming: Series A and B
A Logarithmic-Quadratic Proximal Method for Variational Inequalities
Computational Optimization and Applications - Special issue on computational optimization—a tribute to Olvi Mangasarian, part I
Interior Proximal and Multiplier Methods Based on Second Order Homogeneous Kernels
Mathematics of Operations Research
Convergence of Proximal-Like Algorithms
SIAM Journal on Optimization
A Generalized Proximal Point Algorithm for the Variational Inequality Problem in a Hilbert Space
SIAM Journal on Optimization
Improvements of some projection methods for monotone nonlinear variational inequalities
Journal of Optimization Theory and Applications
An LQP Method for Pseudomonotone Variational Inequalities
Journal of Global Optimization
Mixed quasi complementarity problems in topological vector spaces
Journal of Global Optimization
Hi-index | 0.00 |
Based on the Logarithmic-Quadratic Proximal (LQP) method 2, we propose a new prediction-correction method for nonlinear complementarity problem (NCP). We obtain the predictor through a simplified inexact logarithmic-quadratic proximal method under a relaxed inexact criterion. The corrector is obtained by the improved extragradient method. Under certain conditions, the global convergence of the proposed method is proved. Preliminary numerical results indicate the efficiency of the proposed method.