On damping parameters of Levenberg-Marquardt algorithm for nonlinear least square problems

Abstract

The Levenberg-Marquardt (LM) algorithm is a widely used method for solving problems related to nonlinear least squares. The method depends on a nonlinear parameter μ known as self-scaling parameter that affects the performance of the algorithm. In this paper we examine the effect of various choice of parameters and of relaxing the line search. Numerical results obtained are used to compare the performance using standard test problems which show that the proposed alternatives are promising.