A methodology for solving chemical equilibrium systems
Applied Mathematics and Computation
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ACM Transactions on Mathematical Software (TOMS)
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An interior point potential reduction method for constrained equations
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SIAM Journal on Scientific Computing
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Newton's Method for Large Bound-Constrained Optimization Problems
SIAM Journal on Optimization
Numerical Methods for Unconstrained Optimization and Nonlinear Equations (Classics in Applied Mathematics, 16)
STRSCNE: A Scaled Trust-Region Solver for Constrained Nonlinear Equations
Computational Optimization and Applications
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
The Lagrangian Globalization Method for Nonsmooth Constrained Equations
Computational Optimization and Applications
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
Journal of Computational and Applied Mathematics
Trust-region quadratic methods for nonlinear systems of mixed equalities and inequalities
Applied Numerical Mathematics
Spectral gradient projection method for monotone nonlinear equations with convex constraints
Applied Numerical Mathematics
An interior-point method for solving box-constrained underdetermined nonlinear systems
Journal of Computational and Applied Mathematics
Journal of Computational and Applied Mathematics
Journal of Computational and Applied Mathematics
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ACMOS'05 Proceedings of the 7th WSEAS international conference on Automatic control, modeling and simulation
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Computational Optimization and Applications
Gradient trust region algorithm with limited memory BFGS update for nonsmooth convex minimization
Computational Optimization and Applications
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This paper presents an iterative method for solving bound-constrained systems of nonlinear equations. It combines ideas from the classical trust-region Newton method for unconstrained nonlinear equations and the recent interior affine scaling approach for constrained optimization problems. The method generates feasible iterates and handles the bounds implicitly. It reduces to a standard trust-region method for unconstrained problems when there are no upper or lower bounds on the variables. Global and local fast convergence properties are obtained. The numerical performance of the method is shown on a large number of test problems.