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Journal of Applied Mathematics and Computing

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20.04.2020 | Original Research

Two nonmonotone trust region algorithms based on an improved Newton method

verfasst von: T. Dehghan Niri, M. Heydari, M. M. Hosseini

Erschienen in: Journal of Applied Mathematics and Computing | Ausgabe 1-2/2020

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Abstract

In this paper, we present two improved regularized Newton methods for minimizing nonconvex functions with the trust region method. The fundamental idea of this method is based on the combination of nonmonotone Armijo-type line search proposed by Gu and Mo (Comput Math Appl 55:2158–2172, 2008) and the traditional trust region method. Under some standard assumptions, we analyze the global convergence property for the new methods. Primary numerical results are reported. The obtained results confirm the higher efficiency of the modified algorithms compared to the other presented algorithms.

Vorheriger Artikel Least energy sign-changing solutions for fourth-order Kirchhoff-type equation with potential vanishing at infinity

Nächster Artikel Existence of solutions for nonlinear fractional differential equations with non-homogenous boundary conditions

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Titel: Two nonmonotone trust region algorithms based on an improved Newton method
verfasst von: T. Dehghan Niri
M. Heydari
M. M. Hosseini
Publikationsdatum: 20.04.2020
Verlag: Springer Berlin Heidelberg
Erschienen in: Journal of Applied Mathematics and Computing / Ausgabe 1-2/2020
Print ISSN: 1598-5865
Elektronische ISSN: 1865-2085
DOI: https://doi.org/10.1007/s12190-020-01350-7

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