Newton-Krylov Type Algorithm for Solving Nonlinear Least Squares Problems

The minimization of a quadratic function within an ellipsoidal trust region is an important subproblem for many nonlinear programming algorithms. When the number of variables is large, one of the most widely used strategies is to project the original problem into a small dimensional subspace. In thi...

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Main Authors: Mohammedi R. Abdel-Aziz, Mahmoud M. El-Alem
Format: Article
Language:English
Published: Wiley 2009-01-01
Series:International Journal of Mathematics and Mathematical Sciences
Online Access:http://dx.doi.org/10.1155/2009/435851
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author Mohammedi R. Abdel-Aziz
Mahmoud M. El-Alem
author_facet Mohammedi R. Abdel-Aziz
Mahmoud M. El-Alem
author_sort Mohammedi R. Abdel-Aziz
collection DOAJ
description The minimization of a quadratic function within an ellipsoidal trust region is an important subproblem for many nonlinear programming algorithms. When the number of variables is large, one of the most widely used strategies is to project the original problem into a small dimensional subspace. In this paper, we introduce an algorithm for solving nonlinear least squares problems. This algorithm is based on constructing a basis for the Krylov subspace in conjunction with a model trust region technique to choose the step. The computational step on the small dimensional subspace lies inside the trust region. The Krylov subspace is terminated such that the termination condition allows the gradient to be decreased on it. A convergence theory of this algorithm is presented. It is shown that this algorithm is globally convergent.
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language English
publishDate 2009-01-01
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record_format Article
series International Journal of Mathematics and Mathematical Sciences
spelling doaj-art-e61453b7dc1a4798b5e706b5427e3a082025-08-20T02:21:02ZengWileyInternational Journal of Mathematics and Mathematical Sciences0161-17121687-04252009-01-01200910.1155/2009/435851435851Newton-Krylov Type Algorithm for Solving Nonlinear Least Squares ProblemsMohammedi R. Abdel-Aziz0Mahmoud M. El-Alem1Department of Mathematics and Computer Science, Faculty of Science, Kuwait University, P.O. 5969, Safat 13060, Kuwait City, KuwaitDepartment of Mathematics and Computer Science, Faculty of Science, Kuwait University, P.O. 5969, Safat 13060, Kuwait City, KuwaitThe minimization of a quadratic function within an ellipsoidal trust region is an important subproblem for many nonlinear programming algorithms. When the number of variables is large, one of the most widely used strategies is to project the original problem into a small dimensional subspace. In this paper, we introduce an algorithm for solving nonlinear least squares problems. This algorithm is based on constructing a basis for the Krylov subspace in conjunction with a model trust region technique to choose the step. The computational step on the small dimensional subspace lies inside the trust region. The Krylov subspace is terminated such that the termination condition allows the gradient to be decreased on it. A convergence theory of this algorithm is presented. It is shown that this algorithm is globally convergent.http://dx.doi.org/10.1155/2009/435851
spellingShingle Mohammedi R. Abdel-Aziz
Mahmoud M. El-Alem
Newton-Krylov Type Algorithm for Solving Nonlinear Least Squares Problems
International Journal of Mathematics and Mathematical Sciences
title Newton-Krylov Type Algorithm for Solving Nonlinear Least Squares Problems
title_full Newton-Krylov Type Algorithm for Solving Nonlinear Least Squares Problems
title_fullStr Newton-Krylov Type Algorithm for Solving Nonlinear Least Squares Problems
title_full_unstemmed Newton-Krylov Type Algorithm for Solving Nonlinear Least Squares Problems
title_short Newton-Krylov Type Algorithm for Solving Nonlinear Least Squares Problems
title_sort newton krylov type algorithm for solving nonlinear least squares problems
url http://dx.doi.org/10.1155/2009/435851
work_keys_str_mv AT mohammedirabdelaziz newtonkrylovtypealgorithmforsolvingnonlinearleastsquaresproblems
AT mahmoudmelalem newtonkrylovtypealgorithmforsolvingnonlinearleastsquaresproblems