The nonlinear programming method of Wilson, Han, and Powell with an augmented Lagrangian type line search function. I. Convergence analysis
type: Item
instance of: scholarly article
title: The nonlinear programming method of Wilson, Han, and Powell with an augmented Lagrangian type line search function. I. Convergence analysis
zbMATH Open document ID: 0534.65030
DOI: 10.1007/BF01395810
author: Klaus Schittkowski
published in: Numerische Mathematik
publication date: 1981-01-01T00:00:00Z
full work available at URL: https://eudml.org/doc/132750
review text: Comparative studies of codes for solving continuously differentiable nonlinear programs indicate that quadratic approximation methods are efficient and reliable. In this paper the author presents a convergence analysis of the method of \textit{R. B. Wilson, S.-P. Han} and \textit{M. J. D. Powell} [cf. the author's book: Nonlinear programming codes. Information, tests, performance (1980; Zbl 0435.90063)]. This analysis results in overcoming some of the theoretical disadvantages and in improvement of numerical performance of the method. This is achieved by replacing the exact \(L_ 1\)-penalty function by a differentiable augmented Lagrange function for the line search computation.
Mathematics Subject Classification ID: 65K05
Mathematics Subject Classification ID: 90C30
zbMATH DE Number: 3848509
zbMATH Keywords: quadratic approximation methods
zbMATH Keywords: convergence analysis
zbMATH Keywords: penalty function
zbMATH Keywords: augmented Lagrange function
zbMATH Keywords: line search computation
reviewed by: Sanjo Zlobec
MaRDI profile type: Publication
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OpenAlex ID: W344808587
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description: scientific article; zbMATH DE number 3848509