Global convergence of a class of trust region algorithms for optimization with simple bounds
SIAM Journal on Numerical Analysis
SIAM Journal on Numerical Analysis
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
Mathematical Programming: Series A and B
A limited memory algorithm for bound constrained optimization
SIAM Journal on Scientific Computing
Solution of monotone complementarity problems with locally Lipschitzian functions
Mathematical Programming: Series A and B - Special issue on computational nonsmooth optimization
Algorithm 778: L-BFGS-B: Fortran subroutines for large-scale bound-constrained optimization
ACM Transactions on Mathematical Software (TOMS)
SIAM Journal on Control and Optimization
SIAM Journal on Control and Optimization
A Truncated Newton Algorithm for Large Scale Box Constrained Optimization
SIAM Journal on Optimization
On the Accurate Identification of Active Constraints
SIAM Journal on Optimization
An Active Set Newton Algorithm for Large-Scale Nonlinear Programs with Box Constraints
SIAM Journal on Optimization
Newton's Method for Large Bound-Constrained Optimization Problems
SIAM Journal on Optimization
Pattern Search Algorithms for Bound Constrained Minimization
SIAM Journal on Optimization
An affine scaling trust-region approach to bound-constrained nonlinear systems
Applied Numerical Mathematics
STRSCNE: A Scaled Trust-Region Solver for Constrained Nonlinear Equations
Computational Optimization and Applications
An interior-point affine-scaling trust-region method for semismooth equations with box constraints
Computational Optimization and Applications
Optimization Methods & Software
A Newton-type method for constrained least-squares data-fitting with easy-to-control rational curves
Journal of Computational and Applied Mathematics
Trust-region quadratic methods for nonlinear systems of mixed equalities and inequalities
Applied Numerical Mathematics
A reduced Newton method for constrained linear least-squares problems
Journal of Computational and Applied Mathematics
An active set feasible method for large-scale minimization problems with bound constraints
Computational Optimization and Applications
Constrained Dogleg methods for nonlinear systems with simple bounds
Computational Optimization and Applications
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A class of new affine-scaling interior-point Newton-type methods are considered for the solution of optimization problems with bound constraints. The methods are shown to be locally quadratically convergent under the strong second order sufficiency condition without assuming strict complementarity of the solution. The new methods differ from previous ones by Coleman and Li [Mathematical Programming, 67 (1994), pp. 189---224] and Heinkenschloss, Ulbrich, and Ulbrich [Mathematical Programming, 86 (1999), pp. 615---635] mainly in the choice of the scaling matrix. The scaling matrices used here have stronger smoothness properties and allow the application of standard results from non smooth analysis in order to obtain a relatively short and elegant local convergence result. An important tool for the definition of the new scaling matrices is the correct identification of the degenerate indices. Some illustrative numerical results with a comparison of the different scaling techniques are also included.