A projected gradient trust-region method for solving nonlinear systems with convex constraints

DOI10.1007/s11766-011-1956-7zbMath1240.90378OpenAlexW1982248317MaRDI QIDQ655752

Chun-Xia Jia, De-Tong Zhu

Publication date: 27 January 2012

Published in: Applied Mathematics. Series B (English Edition) (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11766-011-1956-7

zbMATH Keywords

nonlinear equationtrust region methodprojected gradientlocal error bound

Mathematics Subject Classification ID

Nonlinear programming (90C30) Numerical methods based on nonlinear programming (49M37)

Related Items (2)

A unified derivative-free projection method model for large-scale nonlinear equations with convex constraints ⋮ Supermemory gradient methods for monotone nonlinear equations with convex constraints

Cites Work

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• Levenberg--Marquardt methods with strong local convergence properties for solving nonlinear equations with convex constraints
• Convergence properties of trust region methods for linear and convex constraints
• Affine scaling interior Levenberg-Marquardt method for bound-constrained semismooth equations under local error bound conditions
• On the Identification Property of a Projected Gradient Method
• Two-Metric Projection Methods for Constrained Optimization
• Global Convergence of a a of Trust-Region Methods for Nonconvex Minimization in Hilbert Space
• Projected gradient methods for linearly constrained problems

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