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In Favor of Conjugate Directions: a Generalized Acceptable-point Algorithm for Function Minimization

✍ Scribed by M.A. Townsend; G.E. Johnson

Publisher: Elsevier Science
Year: 1978
Tongue: English
Weight: 915 KB
Volume: 306
Category: Article
ISSN: 0016-0032
DOI: 10.1016/0016-0032(78)90025-x

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✦ Synopsis

A generalization of the conjugate directions minimization technique enables utilization of a coarse univariate subsearch to identify acceptable points (as opposed to a minimizing line search) and performs better than commonly-used conjugate directions algorithms. It performs comparably to and has many desirable properties of recent variable-metric algorithms, but with the simpler procedures of conjugate direction methods. Conjugate directions are always generated and simple checks for progress are presented.

As implemented, a golden section univariate subsearch with relative interval reduction of 0.1-0.01 is used, for reasons which are given in the paper. Questions of accuracy of search and reset are addressed. Numerical comparisons are given.

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