Mathematical Programming: Series A and B
A nonsmooth version of Newton's method
Mathematical Programming: Series A and B
Convergence analysis of some algorithms for solving nonsmooth equations
Mathematics of Operations Research
A nonsmooth inexact Newton method for the solution of large-scale nonlinear complementarity problems
Mathematical Programming: Series A and B - Special issue on computational nonsmooth optimization
Solution of monotone complementarity problems with locally Lipschitzian functions
Mathematical Programming: Series A and B - Special issue on computational nonsmooth optimization
Global methods for nonlinear complementarity problems
Mathematics of Operations Research
Computational Optimization and Applications - Special issue on computational optimization—a tribute to Olvi Mangasarian, part II
Improving the convergence of non-interior point algorithms for nonlinear complementarity problems
Mathematics of Computation
A New Merit Function For Nonlinear Complementarity Problems And A Related Algorithm
SIAM Journal on Optimization
Smooth Approximations to Nonlinear Complementarity Problems
SIAM Journal on Optimization
NCP Functions Applied to Lagrangian Globalization for the Nonlinear Complementarity Problem
Journal of Global Optimization
Journal of Computational and Applied Mathematics
Globally convergent Jacobian smoothing inexact Newton methods for NCP
Computational Optimization and Applications
A variant smoothing Newton method for P0-NCP based on a new smoothing function
Journal of Computational and Applied Mathematics
Hi-index | 7.29 |
In this article, we propose a new smoothing inexact Newton algorithm for solving nonlinear complementarity problems (NCP) base on the smoothed Fischer-Burmeister function. In each iteration, the corresponding linear system is solved only approximately. The global convergence and local superlinear convergence are established without strict complementarity assumption at the NCP solution. Preliminary numerical results indicate that the method is effective for large-scale NCP.