A modified quasi-Newton method for structured optimization with partial information on the Hessian

DOI10.1007/s10589-006-6440-6zbMath1121.90126OpenAlexW1977452077MaRDI QIDQ853668

Li-Hua Chen, Nai-Yang Deng, Zhang, Jianzhong

Publication date: 17 November 2006

Published in: Computational Optimization and Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10589-006-6440-6

zbMATH Keywords

Dennis-Moré conditionModified quasi-Newton methodpartial information on the Hessian

Mathematics Subject Classification ID

Nonlinear programming (90C30) Methods of successive quadratic programming type (90C55)

Related Items (6)

An accelerated descent CG algorithm with clustering the eigenvalues for large-scale nonconvex unconstrained optimization and its application in image restoration problems ⋮ A class of spectral three-term descent Hestenes-Stiefel conjugate gradient algorithms for large-scale unconstrained optimization and image restoration problems ⋮ A new modified scaled conjugate gradient method for large-scale unconstrained optimization with non-convex objective function ⋮ A modified BFGS algorithm based on a hybrid secant equation ⋮ Structured symmetric rank-one method for unconstrained optimization ⋮ Scaled nonlinear conjugate gradient methods for nonlinear least squares problems

Uses Software

• CUTEr
• minpack
• CUTE

Cites Work

• Convergence theory for the structured BFGS secant method with an application to nonlinear least squares
• More test examples for nonlinear programming codes
• Nonmonotone Levenberg-Marquardt algorithms and their convergence analysis
• Variational Methods for Non-Linear Least-Squares
• Testing Unconstrained Optimization Software
• CUTE

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