Recent advances in numerical methods for nonlinear equations andnonlinear least squares

Ya-Xiang Yuan

doi:10.3934/naco.2011.1.15

Article Contents

2011, Volume 1, Issue 1: 15-34. Doi: 10.3934/naco.2011.1.15

This issue Previous Article On methods for solving nonlinear semidefinite optimization problems Next Article CVaR-based formulation and approximation method for stochastic variational inequalities

Recent advances in numerical methods for nonlinear equations and nonlinear least squares

Ya-Xiang Yuan^1,

1.
State Key Laboratory of Scientific/Engineering Computing, Institute of Computational Mathematics and Scientific/Engineering Computing,Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Zhong Guan Cun Donglu 55, Beijing, 100190

Received: June 2010

Revised: September 2010

Published: January 2011

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Abstract

Nonlinear equations and nonlinear least squares problems have many applications in physics, chemistry, engineering, biology, economics, finance and many other fields. In this paper, we will review some recent results on numerical methods for these two special problems, particularly on Levenberg-Marquardt type methods, quasi-Newton type methods, and trust region algorithms. Discussions on variable projection methods and subspace methods are also given. Some theoretical results about local convergence results of the Levenberg-Marquardt type methods without non-singularity assumption are presented. A few model algorithms based on line searches and trust regions are also given.

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Mathematics Subject Classification: Primary: 65K10; Secondary: 90C05.

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