Numerical experience with a class of self-scaling quasi-Newton algorithms

Self-scaling quasi-Newton methods for unconstrained optimization depend upon updating the Hessian approximation by a formula which depends on two parameters (say, τ and θ) such that τ = 1, θ = 0, and θ = 1 yield the unscaled Broyden family, the BFGS update, and the DFP update, respectively. In previ...

Ausführliche Beschreibung

Bibliographische Detailangaben

Veröffentlicht in:	Journal of optimization theory and applications 1998-03, Vol.96 (3), p.533-553
1. Verfasser:	AL-BAALI, M
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Applied sciences Exact sciences and technology Operational research and scientific management Operational research. Management science Optimization. Search problems
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!