Using function-values in multi-step quasi-Newton methods

DOI10.1016/0377-0427(95)00178-6zbMath0856.65073OpenAlexW1991328835MaRDI QIDQ1919371

I. A. Moghrabi, John A. Ford

Publication date: 2 March 1997

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

Full work available at URL: https://doi.org/10.1016/0377-0427(95)00178-6

zbMATH Keywords

unconstrained optimizationnumerical experimentsmultistep quasi-Newton methodsfunction value information

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Nonlinear programming (90C30)

Related Items

Local and superlinear convergence of quasi-Newton methods based on modified secant conditions, Numerical experience with multiple update quasi-Newton methods for unconstrained optimization, A Dai-Liao conjugate gradient method via modified secant equation for system of nonlinear equations, A new conjugate gradient algorithm for training neural networks based on a modified secant equation, Some modified Yabe–Takano conjugate gradient methods with sufficient descent condition, Globally convergent modified Perry's conjugate gradient method, A modified secant equation quasi-Newton method for unconstrained optimization, A new descent algorithm with curve search rule, Two new conjugate gradient methods based on modified secant equations, A descent family of Dai–Liao conjugate gradient methods, A new class of memory gradient methods with inexact line searches, A nonlinear model for function-value multistep methods, A modified BFGS algorithm based on a hybrid secant equation, A new super-memory gradient method with curve search rule, A CLASS OF MODIFIED BFGS METHODS WITH FUNCTION VALUE INFORMATION FOR UNCONSTRAINED OPTIMIZATION

Uses Software

• minpack

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• On the use of curvature estimates in quasi-Newton methods
• On the use of function-values in unconstrained optimisation
• Multi-step quasi-Newton methods for optimization
• A Note on Minimization Algorithms which make Use of Non-quardratic Properties of the Objective Function
• A Modified BFGS Algorithm for Unconstrained Optimization
• A Tool for the Analysis of Quasi-Newton Methods with Application to Unconstrained Minimization
• Testing Unconstrained Optimization Software
• Optimal conditioning of self-scaling variable Metric algorithms
• Matrix conditioning and nonlinear optimization
• A Family of Variable-Metric Methods Derived by Variational Means
• The Convergence of a Class of Double-rank Minimization Algorithms
• A new approach to variable metric algorithms
• Conditioning of Quasi-Newton Methods for Function Minimization
• Minimization Algorithms Making Use of Non-quadratic Properties of the Objective Function