Proximity control in bundle methods for convex
Mathematical Programming: Series A and B
Newton's method for B-differentiable equations
Mathematics of Operations Research
On concepts of directional differentiability
Journal of Optimization Theory and Applications
Mathematical Programming: Series A and B
A Globally Convergent Successive Approximation Method for Severely Nonsmooth Equations
SIAM Journal on Control and Optimization
A class of smoothing functions for nonlinear and mixed complementarity problems
Computational Optimization and Applications
Some Noninterior Continuation Methods for LinearComplementarity Problems
SIAM Journal on Matrix Analysis and Applications
New version of the Newton method for nonsmooth equations
Journal of Optimization Theory and Applications
Nonsmooth analysis and control theory
Nonsmooth analysis and control theory
A continuation method for (strongly) monotone variational inequalities
Mathematical Programming: Series A and B
Nonsmooth equation based BFGS method for solving KKT systems in mathematical programming
Journal of Optimization Theory and Applications
Newton and Quasi-Newton Methods for a Class of Nonsmooth Equations and Related Problems
SIAM Journal on Optimization
Smooth Approximations to Nonlinear Complementarity Problems
SIAM Journal on Optimization
Pseudo-Transient Continuation for Nonsmooth Nonlinear Equations
SIAM Journal on Numerical Analysis
Globally convergent limited memory bundle method for large-scale nonsmooth optimization
Mathematical Programming: Series A and B
A quasisecant method for minimizing nonsmooth functions
Optimization Methods & Software - DEDICATED TO PROFESSOR VLADIMIR F. DEMYANOV ON THE OCCASION OF HIS 70TH BIRTHDAY
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In this paper, the solution of nonsmooth equations is studied. We first transform the problem into an equivalent nonsmooth optimization problem and then the quasisecant method is introduced to solve it. Some nonsmooth equations that have arisen from bilevel programming problems are solved by our proposed method. The numerical results show the effectiveness and efficiency of our proposed method.