Convergence of implementable descent algorithms for unconstrained optimization
type: Item
instance of: scholarly article
title: Convergence of implementable descent algorithms for unconstrained optimization
zbMATH Open document ID: 0974.90018
DOI: 10.1023/A:1004602012151
published in: Journal of Optimization Theory and Applications
publication date: 2001-12-16T00:00:00Z
review text: Having the paper of \textit{A. N. Iusem} and \textit{B. F. Svaiter} about a proximal regularization of the steepest descent method [RAIRO-Rech. Opér. 29, 123-130 (1995; Zbl 0835.90066)] in mind and using quasi-Fejér convergence it is shown, that for quasiconvex objectives the whole sequence, obtained by a suitable descent algorithm with Armijo step size rule, is convergent.
reviewed by: Alfred Göpfert
Mathematics Subject Classification ID: 90C26
Mathematics Subject Classification ID: 65K05
zbMATH DE Number: 1486615
zbMATH Keywords: descent algorithm
zbMATH Keywords: global convergence
zbMATH Keywords: stepsize rules
author: Jean-Pierre Dussault
MaRDI profile type: Publication
cites work: A proximal regularization of the steepest descent method
cites work: Minimization of functions having Lipschitz continuous first partial derivatives
cites work: Convergence Conditions for Ascent Methods
full work available at URL: a:1004602012151
OpenAlex ID: W135531879
description: scientific article; zbMATH DE number 1486615