Methods of Conjugate Directions Versus Quasi-Newton Methods.
Abstract
It is shown that algorithms for minimizing an unconstrained function F(x), x belongs to E sup n, which are solely methods of conjugate directions, can be expected to exhibit only an n or (n - 1) step superlinear rate of convergence to an isolated local minimizer. This is contrasted with quasi-Newton methods which can be expected to exhibit every step superlinear convergence. Similar statements about a quadratic rate of convergence hold when a Lipschitz condition is placed on the second derivative of F(x). (Author)
Document Details
- Document Type
- Technical Report
- Publication Date
- Aug 01, 1971
- Accession Number
- AD0731718
Entities
People
- Garth P. Mccormick
- Klaus Ritter