Treffer: An iterative method for solving semismooth equations
Title:
An iterative method for solving semismooth equations
Authors:
Source:
Papers presented at the 1st Sino-Japan Optimization Meeting, 26-28 October 2000, Hong Kong, ChinaJournal of computational and applied mathematics. 146(1):1-10
Publisher Information:
Amsterdam: Elsevier, 2002.
Publication Year:
2002
Physical Description:
print, 13 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, Backtracking, Fonction régulière, Smooth function, Función regular, Inégalité variationnelle, Variational inequality, Desigualdad variacional, Itération, Iteration, Iteracción, Méthode Newton, Newton method, Método Newton, Méthode itérative, Iterative method, Método iterativo, Méthode lignes, Method of lines, Método líneas, Méthode lissage, Smoothing methods, Problème complémentarité non linéaire, Non linear complementarity problem, Problema complementariedad no lineal, Résolution équation, Equation resolution, Resolución ecuación, Equation semilisse, Trust region method
Document Type:
Konferenz
Conference Paper
File Description:
text
Language:
English
Author Affiliations:
Department of Mathematics, Nanjing University, 210093 Nanjing, China
Institute of Applied Mathematics, Hunan University, Changsha, China
Department of Applied Mathematics, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong-Kong
Institute of Applied Mathematics, Hunan University, Changsha, China
Department of Applied Mathematics, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong-Kong
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.13838688
Database:
PASCAL Archive
Weitere Informationen
In this paper, we combine trust region technique with line search technique to develop an iterative method for solving semismooth equations. At each iteration, a trust region subproblem is solved. The solution of the trust region subproblem provides a descent direction for the norm of a smoothing function. By using a backtracking line search, a steplength is determined. The proposed method shares advantages of trust region methods and line search methods. Under appropriate conditions, the proposed method is proved to be globally and superlinearly convergent. In particular, we show that after finitely many iterations, the unit step is always accepted and the method reduces to a smoothing Newton method.