Local and Superlinear Convergence for Partially Known Quasi-Newton Methods

DOI10.1137/0801005zbMath0752.90063OpenAlexW2059338280MaRDI QIDQ4017638

Héctor Martínez, John R. Engels

Publication date: 16 January 1993

Published in: SIAM Journal on Optimization (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1137/0801005

zbMATH Keywords

unconstrained optimizationconstrained optimizationsecant methodnonlinear least-squaresbounded deteriorationlocal and \(q\)- superlinear convergence of quasi-Newton methods

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Nonlinear programming (90C30) Computational methods for problems pertaining to operations research and mathematical programming (90-08)

Related Items (15)

Rates of superlinear convergence for classical quasi-Newton methods ⋮ A robust combined trust region–line search exact penalty projected structured scheme for constrained nonlinear least squares ⋮ Greedy PSB methods with explicit superlinear convergence ⋮ Globally convergent three-term conjugate gradient methods that use secant conditions and generate descent search directions for unconstrained optimization ⋮ On simulation and optimization of macroeconometric models ⋮ Nonlinear conjugate gradient methods with structured secant condition for nonlinear least squares problems ⋮ New results on superlinear convergence of classical quasi-Newton methods ⋮ Numerical algorithms for constrained maximum likelihood estimation ⋮ Structured symmetric rank-one method for unconstrained optimization ⋮ Scaled nonlinear conjugate gradient methods for nonlinear least squares problems ⋮ Operations research and optimization (ORO) ⋮ A Kantorovich theorem for the structured PSB update in Hilbert space. ⋮ Greedy Quasi-Newton Methods with Explicit Superlinear Convergence ⋮ Adaptive algorithm for constrained least-squares problems ⋮ Exploiting additional structure in equality constrained optimization by structured SQP secant algorithms

Uses Software

• ve08

This page was built for publication: Local and Superlinear Convergence for Partially Known Quasi-Newton Methods