The nonlinear programming method of Wilson, Han, and Powell with an augmented Lagrangian type line search function. II. An efficient implementation with linear least squares subproblems
type: Item
instance of: scholarly article
title: The nonlinear programming method of Wilson, Han, and Powell with an augmented Lagrangian type line search function. II. An efficient implementation with linear least squares subproblems
zbMATH Open document ID: 0534.65031
DOI: 10.1007/BF01395811
author: Klaus Schittkowski
published in: Numerische Mathematik
publication date: 1981-01-01T00:00:00Z
full work available at URL: https://eudml.org/doc/132751
review text: [For part I see ibid. 38, 83-114 (1981; reviewed above).] This paper presents the results of numerical experiments for different versions of the method of R. B. Wilson, S.-P. Han and M. J. D. Powell. The following topics are studied and tested: the influence of the line search function on the numerical performance, the effect of a least square formulation of the quadratic subproblem, the dependence of the performance from different solution methods for the least squares subproblem, the usage of numerical differentiation, and the effect of an inverse update technique.
Mathematics Subject Classification ID: 65K05
Mathematics Subject Classification ID: 90C30
zbMATH DE Number: 3848510
zbMATH Keywords: numerical experiments
zbMATH Keywords: line search function
zbMATH Keywords: numerical performance
zbMATH Keywords: least square formulation
zbMATH Keywords: quadratic subproblem
zbMATH Keywords: inverse update technique
reviewed by: Sanjo Zlobec
MaRDI profile type: Publication
cites work: A Matrix Modification Method for Calculating Approximate Solutions to Systems of Linear Equations
cites work: A General Quadratic Programming Algorithm
cites work: Methods for Computing and Modifying the LDV Factors of a Matrix
cites work: A globally convergent method for nonlinear programming
cites work: Q4879581
cites work: Nonlinear programming codes. Information, tests, performance
cites work: A factorization method for the solution of constrained linear least squares problems allowing subsequent data changes
OpenAlex ID: W2884670864
description: scientific article; zbMATH DE number 3848510