The Levenberg–Marquardt method: an overview of modern convergence theories and more

Andreas Fischer (), Alexey F. Izmailov () and Mikhail V. Solodov ()
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Andreas Fischer: Technische Universität Dresden
Alexey F. Izmailov: Lomonosov Moscow State University (MSU)
Mikhail V. Solodov: IMPA – Instituto de Matemática Pura e Aplicada

Computational Optimization and Applications, 2024, vol. 89, issue 1, No 2, 33-67

Abstract: Abstract The Levenberg–Marquardt method is a fundamental regularization technique for the Newton method applied to nonlinear equations, possibly constrained, and possibly with singular or even nonisolated solutions. We review the literature on the subject, in particular relating to each other various convergence frameworks and results. In this process, the analysis is performed from a unified perspective, and some new results are obtained as well. We discuss smooth and piecewise smooth equations, inexact solution of subproblems, and globalization techniques. Attention is also paid to the LP-Newton method, because of its relations to the Levenberg–Marquardt method.

Keywords: Nonlinear equation; Constrained equation; Piecewise smooth equation; Nonisolated solution; Local error bound; Gauss–Newton method; Levenberg–Marquardt method; LP-Newton method; Singular solution; 47J05; 65K15 (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s10589-024-00589-1

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