Accession Number:

AD0730159

Title:

A Computational Comparison of Gradient Minimization Algorithms.

Descriptive Note:

Master's thesis,

Corporate Author:

AIR FORCE INST OF TECH WRIGHT-PATTERSON AFB OHIO SCHOOL OF ENGINEERING

Personal Author(s):

Report Date:

1971-03-01

Pagination or Media Count:

146.0

Abstract:

A technique was developed for the comparison of gradient minimization routines in solving the unconstrained optimization problem. The problem of locating the local minimum of a given real-valued, non-negative, differentiable function was used in this study to compare three gradient algorithms, namely Davidons variance algorithm, the Fletcher-Reeves algorithm, and the Fletcher-Powell algorithm. A cost criterion and an average convergence rate were devised to facilitate the comparisons of these algorithms. Davidons variance algorithm, a rank-one method, was judged to be the best routine for over fifty-three percent of the total cases tested. The comparisons are graphically presented in an appendix. Author

Subject Categories:

  • Theoretical Mathematics
  • Operations Research

Distribution Statement:

APPROVED FOR PUBLIC RELEASE