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Multiplier and gradient methods

Journal of Optimization Theory and ApplicationsPublished 1 November 1969
Magnus R. Hestenes
Citations2,410
SJR quartileQ1
SJR score0.78
SNIP1.30

TL;DR

The main purpose of this paper is to suggest a method for finding the minimum of a functionf(x) subject to the constraintg(x)=0, which consists of replacingf byF=f+λg+1/2cg2, and computing the appropriate value of the Lagrange multiplier.

Abstract

The main purpose of this paper is to suggest a method for finding the minimum of a functionf(x) subject to the constraintg(x)=0. The method consists of replacingf byF=f+λg+1/2cg 2, wherec is a suitably large constant, and computing the appropriate value of the Lagrange multiplier. Only the simplest algorithm is presented. The remaining part of the paper is devoted to a survey of known methods for finding unconstrained minima, with special emphasis on the various gradient techniques that are available. This includes Newton's method and the method of conjugate gradients.

Keywords

Computer ScienceMathematics