CONJUGATE DIRECTION METHODS WITH VARIABLE STORAGE.

Larry Nazareth; Jorge Nocedal

CONJUGATE DIRECTION METHODS WITH VARIABLE STORAGE.

Larry Nazareth^*, Jorge Nocedal

^*Corresponding author for this work

Industrial Engineering and Management Sciences

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

6 Scopus citations

Abstract

Conjugate gradient algorithms for large optimization problems are studied. These methods accelerate (or precondition) the conjugate gradient method by means of quasi-Newton matrices, and are designed to utilize a variable amount of storage, depending on how much information is retained in the quasi-Newton matrices. The behavior of such methods on the underlying quadratic model, and in particular, the finite termination properties are considered.

Original language	English (US)
Title of host publication	Mathematical Programming
Pages	326-340
Number of pages	15
Edition	3
State	Published - Aug 1 1982

Publication series

Name	Mathematical Programming
Number	3
Volume	23

ASJC Scopus subject areas

Software
General Mathematics

Cite this

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title = "CONJUGATE DIRECTION METHODS WITH VARIABLE STORAGE.",

abstract = "Conjugate gradient algorithms for large optimization problems are studied. These methods accelerate (or precondition) the conjugate gradient method by means of quasi-Newton matrices, and are designed to utilize a variable amount of storage, depending on how much information is retained in the quasi-Newton matrices. The behavior of such methods on the underlying quadratic model, and in particular, the finite termination properties are considered.",

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AU - Nocedal, Jorge

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N2 - Conjugate gradient algorithms for large optimization problems are studied. These methods accelerate (or precondition) the conjugate gradient method by means of quasi-Newton matrices, and are designed to utilize a variable amount of storage, depending on how much information is retained in the quasi-Newton matrices. The behavior of such methods on the underlying quadratic model, and in particular, the finite termination properties are considered.

AB - Conjugate gradient algorithms for large optimization problems are studied. These methods accelerate (or precondition) the conjugate gradient method by means of quasi-Newton matrices, and are designed to utilize a variable amount of storage, depending on how much information is retained in the quasi-Newton matrices. The behavior of such methods on the underlying quadratic model, and in particular, the finite termination properties are considered.

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M3 - Conference contribution

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BT - Mathematical Programming

ER -

CONJUGATE DIRECTION METHODS WITH VARIABLE STORAGE.

Abstract

Publication series

ASJC Scopus subject areas

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