Convergence analysis of some algorithms for solving nonsmooth equations
Mathematics of Operations Research
Inexact Newton methods for solving nonsmooth equations
Proceedings of the international meeting on Linear/nonlinear iterative methods and verification of solution
Convergence of the BFGS Method for LC1 Convex Constrained Optimization
SIAM Journal on Control and Optimization
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
Mathematics of Operations Research
Inexact-Newton methods for semismooth system of equations with block-angular structure
Journal of Computational and Applied Mathematics
Computational Optimization and Applications - Special issue on computational optimization—a tribute to Olvi Mangasarian, part II
Convergence behaviour of inexact Newton methods
Mathematics of Computation
On Characterizations of P- and P0-Properties in Nonsmooth Functions
Mathematics of Operations Research
Journal of Optimization Theory and Applications
Inexact methods: forcing terms and conditioning
Journal of Optimization Theory and Applications
Newton and Quasi-Newton Methods for a Class of Nonsmooth Equations and Related Problems
SIAM Journal on Optimization
A choice of forcing terms in inexact Newton method
Journal of Computational and Applied Mathematics
A nonmonotone semismooth inexact Newton method
Optimization Methods & Software
Inexact quasi-Newton global convergent method for solving constrained nonsmooth equations
International Journal of Computer Mathematics
Local convergence of inexact methods under the Hölder condition
Journal of Computational and Applied Mathematics
Convergence behaviour of inexact Newton methods under weak Lipschitz condition
Journal of Computational and Applied Mathematics
Journal of Computational and Applied Mathematics
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The inexact generalized Newton method is an iterative method for solving systems of nonsmooth equations. In this paper, the iterative process with a relative residual control is presented and the conditions for local convergence to a solution are provided. These results can be applied to solve Lipschitz continuous equations under some mild assumptions. Moreover, a globally convergent version of the algorithm with a damped approach based on the Armijo rule is considered.