Title
The convergence of variable metric matrices in unconstrained optimization.
Abstract
It is proved that, if the DFP or BFGS algorithm with step-lengths of one is applied to a functionF(x) that has a Lipschitz continuous second derivative, and if the calculated vectors of variables converge to a point at which ∇F is zero and ∇2 F is positive definite, then the sequence of variable metric matrices also converges. The limit of this sequence is identified in the case whenF(x) is a strictly convex quadratic function.
Year
DOI
Venue
1983
10.1007/BF02591941
Mathematical Programming
Keywords
Field
DocType
Convergence, Quasi-Newton Methods, Unconstrained Optimization, Variable Metric Methods
Convergence (routing),Mathematical optimization,Second derivative,Matrix (mathematics),Positive-definite matrix,Convex function,Quadratic function,Lipschitz continuity,Broyden–Fletcher–Goldfarb–Shanno algorithm,Mathematics
Journal
Volume
Issue
ISSN
27
2
1436-4646
Citations 
PageRank 
References 
6
4.94
1
Authors
2
Name
Order
Citations
PageRank
Ge Ren-pu164.94
M. J. D. Powell217001227.93