Result: Global convergence of nonmonotone descent methods for unconstrained optimization problems
Title:
Global convergence of nonmonotone descent methods for unconstrained optimization problems
Source:
Papers presented at the 1st Sino-Japan Optimization Meeting, 26-28 October 2000, Hong Kong, ChinaJournal of computational and applied mathematics. 146(1):89-98
Publisher Information:
Amsterdam: Elsevier, 2002.
Publication Year:
2002
Physical Description:
print, 19 ref
Original Material:
INIST-CNRS
Subject Terms:
Computer science, Informatique, Mathematics, Mathématiques, Sciences exactes et technologie, Exact sciences and technology, Sciences et techniques communes, Sciences and techniques of general use, Mathematiques, Mathematics, Analyse numérique. Calcul scientifique, Numerical analysis. Scientific computation, Analyse numérique, Numerical analysis, Méthodes numériques en programmation mathématique, optimisation et calcul variationnel, Numerical methods in mathematical programming, optimization and calculus of variations, Programmation mathématique numérique, Numerical methods in mathematical programming, 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, Méthode descente, Descent method, Método descenso, Méthode optimisation, Optimization method, Método optimización, Optimisation sans contrainte, Unconstrained optimization, Optimización sin restricción, Convergence globale, Non monotone line search
Document Type:
Conference
Conference Paper
File Description:
text
Language:
English
Author Affiliations:
School of Mathematics and Computer Science, Nanjing Normal University, Nanjing 210097, China
Institute of Applied Mathematics, Chinese Academy of Science, Beijing 100080, China
Faculty of Business Administration and Singapore-MIT Alliance, National University of Singapore, Singapore
Institute of Applied Mathematics, Chinese Academy of Science, Beijing 100080, China
Faculty of Business Administration and Singapore-MIT Alliance, National University of Singapore, Singapore
ISSN:
0377-0427
Rights:
Copyright 2002 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
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:
Mathematics
Operational research. Management
Operational research. Management
Accession Number:
edscal.13838695
Database:
PASCAL Archive
Further Information
Global convergence results are established for unconstrained optimization algorithms that utilize a nonmonotone line search procedure. This procedure allows the user to specify a flexible forcing function and includes the nonmonotone Armijo rule, the nonmonotone Goldstein rule, and the nonmonotone Wolfe rule as special cases.