Extra updates for the bfgs method∗

DOI10.1080/10556780008805781zbMath0957.90115OpenAlexW2094840107MaRDI QIDQ4508673

Mehiddin Al-Baali

Publication date: 3 October 2000

Published in: Optimization Methods and Software (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/10556780008805781

zbMATH Keywords

unconstrained optimizationBFGS methodglobal and superlinear convergencequasi-Newton updatesquadratic termination

Mathematics Subject Classification ID

Programming involving graphs or networks (90C35) Nonlinear programming (90C30) Numerical computation of solutions to systems of equations (65H10)

Related Items (10)

Convergence properties of the Broyden-like method for mixed linear-nonlinear systems of equations ⋮ On the performance of switching BFGS/SR1 algorithms for unconstrained optimization ⋮ A descent hybrid conjugate gradient method based on the memoryless BFGS update ⋮ Numerical experience with multiple update quasi-Newton methods for unconstrained optimization ⋮ Scaled diagonal gradient-type method with extra update for large-scale unconstrained optimization ⋮ A Class of Approximate Inverse Preconditioners Based on Krylov-Subspace Methods for Large-Scale Nonconvex Optimization ⋮ A symmetric rank-one method based on extra updating techniques for unconstrained optimization ⋮ Global convergence property of scaled two-step BFGS method ⋮ Extra-updates criterion for the limited memory BFGS algorithm for large scale nonlinear optimization ⋮ On the behaviour of a combined extra-updating/self-scaling BFGS method

Cites Work

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• On the limited memory BFGS method for large scale optimization
• Some investigations in a new algorithm for nonlinear optimization based on conic models of the objective function
• Parallel quasi-Newton methods for unconstrained optimization
• Numerical expirience with a class of self-scaling quasi-Newton algorithms
• Stability of Huang's update for the conjugate gradient method
• How bad are the BFGS and DFP methods when the objective function is quadratic?
• A Tool for the Analysis of Quasi-Newton Methods with Application to Unconstrained Minimization
• Testing Unconstrained Optimization Software
• On the Behavior of Broyden’s Class of Quasi-Newton Methods
• Quasi-Newton Methods, Motivation and Theory
• Matrix conditioning and nonlinear optimization
• A Rapidly Convergent Descent Method for Minimization

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