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
Descriptors:
Subject Categories:
- Theoretical Mathematics
- Operations Research