Accession Number:

AD0731718

Title:

Methods of Conjugate Directions Versus Quasi-Newton Methods.

Descriptive Note:

Technical paper,

Corporate Author:

RESEARCH ANALYSIS CORP MCLEAN VA

Personal Author(s):

Report Date:

1971-08-01

Pagination or Media Count:

25.0

Abstract:

It is shown that algorithms for minimizing an unconstrained function Fx, 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 Fx. Author

Subject Categories:

  • Theoretical Mathematics
  • Operations Research

Distribution Statement:

APPROVED FOR PUBLIC RELEASE