Accession Number:

AD0753416

Title:

Computational Algorithms for Unconstrained Optimization

Descriptive Note:

Technical rept.

Corporate Author:

AIR FORCE FLIGHT DYNAMICS LAB WRIGHT-PATTERSON AFB OH

Personal Author(s):

• Kujawski, Bruce T.

Report Date:

1972-10-01

Pagination or Media Count:

61.0

Abstract:

DA generalized descent algorithm theory is developed for unconstrained minimization problems. Here a descent algorithm is defined as a computational procedure where at each iteration a descent direction is determined and a single-dimensional search is made for the minimum in the descent direction. The theory is shown to be a generalization of the three most common descent algorithms gradient, conjugate gradient, and Fletcher-Powell. Execution of the single-dimensional search can be computationally time consuming. Two additional algorithms are presented which reduce or eliminate single-dimensional search time. The first is a modification of Davidons Variance Algorithm and requires a minimal single-dimensional search. The second is a direct method for minimizing a special class of quadratic functions.

Descriptors:

• *MATHEMATICAL PROGRAMMING
• ALGORITHMS
• OPTIMIZATION
• MATRICES(MATHEMATICS)
• THEOREMS
• CONVERGENCE
• NUMERICAL ANALYSIS
• THESES

Subject Categories:

• Operations Research

Distribution Statement:

APPROVED FOR PUBLIC RELEASE