• A limited memory steepest desc...

Treffer: A limited memory steepest descent method

Title:
A limited memory steepest descent method
Authors:
FLETCHER, Roger
Source:
Mathematical programming (Print). 135(1-2):413-436
Publisher Information:
Heidelberg: Springer, 2012.
Publication Year:
2012
Physical Description:
print, 26 ref
Original Material:
INIST-CNRS
Subject Terms:
Control theory, operational research, Automatique, recherche opérationnelle, Mathematics, Mathématiques, Sciences exactes et technologie, Exact sciences and technology, Sciences appliquees, Applied sciences, Recherche operationnelle. Gestion, Operational research. Management science, Recherche opérationnelle et modèles formalisés de gestion, Operational research and scientific management, Programmation mathématique, Mathematical programming, Théorie de la fiabilité. Renouvellement des équipements, Reliability theory. Replacement problems, Allocation mémoire, Storage allocation, Asignación memoria, Disponibilité, Availability, Disponibilidad, Fonction objectif, Objective function, Función objetivo, Fonction quadratique, Quadratic function, Función cuadrática, Gestion mémoire, Storage management, Gestión memoria, Minimisation, Minimization, Minimización, Méthode BFGS, BFGS method(Broyden Fletcher Goldfarb Shanno method), Método BFGS, Méthode gradient conjugué, Conjugate gradient method, Método gradiente conjugado, Méthode plus grande pente, Steepest descent method, Método más grande inclinación, Optimisation sans contrainte, Unconstrained optimization, Optimización sin restricción, Programmation mathématique, Mathematical programming, Programación matemática, Programmation non convexe, Non convex programming, Programación no convexa, Stockage, Storage, Almacenamiento, 65K05, 90C06, 90C26
Document Type:
Fachzeitschrift Article
File Description:
text
Language:
English
Author Affiliations:
Department of Mathematics, University of Dundee, Dundee DD1 4HN, Scotland, United Kingdom
ISSN:
0025-5610
Access URL:
http://pascal-francis.inist.fr/vibad/index.php?action=search&terms=26363396
Rights:
Copyright 2014 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Operational research. Management
Accession Number:
edscal.26363396
Database:
PASCAL Archive

Weitere Informationen

The possibilities inherent in steepest descent methods have been considerably amplified by the introduction of the Barzilai-Borwein choice of step-size, and other related ideas. These methods have proved to be competitive with conjugate gradient methods for the minimization of large dimension unconstrained minimization problems. This paper suggests a method which is able to take advantage of the availability of a few additional 'long' vectors of storage to achieve a significant improvement in performance, both for quadratic and non-quadratic objective functions. It makes use of certain Ritz values related to the Lanczos process (Lanczos in J Res Nat Bur Stand 45:255-282, 1950). Some underlying theory is provided, and numerical evidence is set out showing that the new method provides a competitive and more simple alternative to the state of the art 1-BFGS limited memory method.