Remote Access Mathematics of Computation
Green Open Access

Mathematics of Computation

ISSN 1088-6842(online) ISSN 0025-5718(print)



A quasi-Newton method with no derivatives

Author: John Greenstadt
Journal: Math. Comp. 26 (1972), 145-166
MSC: Primary 65K05
MathSciNet review: 0305592
Full-text PDF Free Access

Abstract | References | Similar Articles | Additional Information

Abstract: The Davidon formula and others of the “quasi-Newton” class, which are used in the unconstrained minimization of a function $f$, provide a (generally) convergent sequence of approximations to the Hessian of $f$. These formulas, however, require the independent calculation of the gradient of $f$. In this paper, a set of new formulas is derived—using a previously described variational approach—which successively approximates the gradient as well as the Hessian, and uses only function values. These formulas are incorporated into an algorithm which, although still crude, works quite well for various standard test functions. Extensive numerical results are presented.

References [Enhancements On Off] (What's this?)

Similar Articles

Retrieve articles in Mathematics of Computation with MSC: 65K05

Retrieve articles in all journals with MSC: 65K05

Additional Information

Keywords: Quasi-Newton methods, gradient-free nonlinear optimization
Article copyright: © Copyright 1972 American Mathematical Society