Chemical equilibrium systems as numerical test problems
ACM Transactions on Mathematical Software (TOMS)
Mathematical Programming: Series A and B
Test Examples for Nonlinear Programming Codes
Test Examples for Nonlinear Programming Codes
A Potential Reduction Newton Method for Constrained Equations
SIAM Journal on Optimization
An affine scaling trust-region approach to bound-constrained nonlinear systems
Applied Numerical Mathematics
Numerical Methods for Unconstrained Optimization and Nonlinear Equations (Classics in Applied Mathematics, 16)
Journal of Computational and Applied Mathematics
An interior-point method for solving box-constrained underdetermined nonlinear systems
Journal of Computational and Applied Mathematics
Journal of Computational and Applied Mathematics
On Affine-Scaling Interior-Point Newton Methods for Nonlinear Minimization with Bound Constraints
Computational Optimization and Applications
An interior-point affine-scaling trust-region method for semismooth equations with box constraints
Computational Optimization and Applications
Global convergence of a tri-dimensional filter SQP algorithm based on the line search method
Applied Numerical Mathematics
An interior-point method for solving box-constrained underdetermined nonlinear systems
Journal of Computational and Applied Mathematics
Journal of Computational Physics
Performance assessment for single echelon airport spare part management
Computers and Industrial Engineering
TRESNEI, a Matlab trust-region solver for systems of nonlinear equalities and inequalities
Computational Optimization and Applications
Convergence analysis of a proximal Gauss-Newton method
Computational Optimization and Applications
Constrained Dogleg methods for nonlinear systems with simple bounds
Computational Optimization and Applications
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In this paper a Matlab solver for constrained nonlinear equations is presented. The code, called STRSCNE, is based on the affine scaling trust-region method STRN, recently proposed by the authors. The approach taken in implementing the key steps of the method is discussed. The structure and the usage of STRSCNE are described and its features and capabilities are illustrated by numerical experiments. The results of a comparison with high quality codes for nonlinear optimization are shown.