An interior-point method for solving box-constrained underdetermined nonlinear systems

DOI10.1016/j.cam.2004.08.013zbMath1064.65035OpenAlexW2145851435MaRDI QIDQ1763761

Nataša Krejić, José Mario Martínez, Juliano B. Francisco

Publication date: 22 February 2005

Published in: Journal of Computational and Applied Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.cam.2004.08.013

zbMATH Keywords

algorithmglobal convergencenumerical experimentsquadratic convergenceNewton methodunderdetermined nonlinear systemsinterior trust-region method

Mathematics Subject Classification ID

Numerical computation of solutions to systems of equations (65H10) Interior-point methods (90C51)

Related Items (max. 100)

Approximate Gauss-Newton methods for solving underdetermined nonlinear least squares problems ⋮ On affine-scaling inexact dogleg methods for bound-constrained nonlinear systems ⋮ Constrained dogleg methods for nonlinear systems with simple bounds ⋮ On the convergence of an inexact Gauss-Newton trust-region method for nonlinear least-squares problems with simple bounds ⋮ A Riemannian inexact Newton dogleg method for constructing a symmetric nonnegative matrix with prescribed spectrum ⋮ A new trust-region method for solving systems of equalities and inequalities ⋮ A new trust region method for solving least-square transformation of system of equalities and inequalities ⋮ A derivative-free method for solving box-constrained underdetermined nonlinear systems of equations ⋮ Global convergence of a tri-dimensional filter SQP algorithm based on the line search method ⋮ Trust-region quadratic methods for nonlinear systems of mixed equalities and inequalities ⋮ Numerical solution of KKT systems in PDE-constrained optimization problems via the affine scaling trust-region approach† ⋮ A Riemannian under-determined BFGS method for least squares inverse eigenvalue problems

Uses Software

• STRSCNE
• levmar

Cites Work

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• The Gradient Projection Method for Nonlinear Programming. Part II. Nonlinear Constraints
• Inexact-restoration method with Lagrangian tangent decrease and new merit function for nonlinear programming.

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