Convergence properties of inexact Levenberg-Marquardt method under Hölderian local error bound

Haiyan Wang; Jinyan Fan

doi:10.3934/jimo.2020068

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2021, Volume 17, Issue 4: 2265-2275. Doi: 10.3934/jimo.2020068

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Convergence properties of inexact Levenberg-Marquardt method under Hölderian local error bound

Haiyan Wang^1, and
Jinyan Fan^2, ,

1.
School of Mathematical Sciences, Shanghai Jiao Tong University, Shanghai 200240, China
2.
School of Mathematical Sciences, Shanghai Jiao Tong University, Key Lab of Scientific and Engineering Computing (Ministry of Education), Shanghai 200240, China

^* Corresponding author: Jinyan Fan
^* Corresponding author: Jinyan Fan

Received: August 2019

Revised: November 2019

Early access: March 2020

Published: July 2021

The authors are supported by Chinese NSF grants 11971309.

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Abstract

In this paper, we study convergence properties of the inexact Levenberg-Marquardt method under the Hölderian local error bound condition and the Hölderian continuity of the Jacobian. The formula of the convergence rates are given, which are functions with respect to the Levenberg-Marquardt parameter, the perturbation vector, as well as the orders of the Hölderian local error bound and Hölderian continuity of the Jacobian.

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Mathematics Subject Classification: 65K05, 90C30.

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References

[1]	M. Ahookhosh, F. J. Aragón, R. M. T. Fleming and P. T. Vuong, Local convergence of Levenberg-Marquardt methods under Hölderian metric subregularity, Adv. Comput. Math., 45 (2019), 2771–2806, arXiv: 1703.07461. doi: 10.1007/s10444-019-09708-7.
[2]	H. Dan, N. Yamashita and M. Fukushima, Convergence properties of the inexact Levenberg-Marquardt method under local error bound, Optimization Methods and Software, 17 (2002), 605-626. doi: 10.1080/1055678021000049345.
[3]	F. Facchinei and C. Kanzow, A nonsmooth inexact Newton method for the solution of large-scale nonlinear complementarity problems, Mathematical Programming, 76 (1997), 493-512. doi: 10.1007/BF02614395.
[4]	J. Y. Fan, A modified Levenberg-Marquardt algorithm for singular system of nonlinear equations, Journal of Computational Mathematics, 21 (2003), 625-636.
[5]	J. Y. Fan, The modified Levenberg-Marquardt method for nonlinear equations with cubic convergence, Mathematics of Computation, 81 (2012), 447-466. doi: 10.1090/S0025-5718-2011-02496-8.
[6]	J. Y. Fan, J. C. Huang and J. Y. Pan, An adaptive multi-step Levenberg-Marquardt method, Journal of Scientific Computing, 78 (2019), 531-548. doi: 10.1007/s10915-018-0777-8.
[7]	J. Y. Fan and J. Y. Pan, Inexact Levenberg-Marquardt method for nonlinear equations, Discrete Continuous Dynamical System-Series B, 4 (2004), 1223-1232. doi: 10.3934/dcdsb.2004.4.1223.
[8]	J. Y. Fan and J. Y. Pan, A note on the Levenberg-Marquardt parameter, Applied Mathematics and Computation, 207 (2009), 351-359. doi: 10.1016/j.amc.2008.10.056.
[9]	J. Y. Fan and J. Y. Pan, On the convergence rate of the inexact Levenberg-Marquardt method, Industrial and Management Optimization, 7 (2011), 199-210. doi: 10.3934/jimo.2011.7.199.
[10]	J. Y. Fan and Y. X. Yuan, On the quadratic convergence of the Levenberg-Marquardt method without nonsingularity assumption, Computing, 74 (2005), 23-39. doi: 10.1007/s00607-004-0083-1.
[11]	A. Fischera, P. K. Shuklaa and M. Wang, On the inexactness level of robust Levenberg-Marquardt methods, Optimization, 59 (2010), 273-287. doi: 10.1080/02331930801951256.
[12]	C. T. Kelley, Solving Nonlinear Equations with Newton's Method, Fundamentals of Algorithms, SIAM, Philadelphia, 2003. doi: 10.1137/1.9780898718898.
[13]	K. Levenberg, A method for the solution of certain nonlinear problems in least squares, Quart. Appl. Math., 2 (1944), 164-168. doi: 10.1090/qam/10666.
[14]	D. W. Marquardt, An algorithm for least-squares estimation of nonlinear inequalities, SIAM J. Appl. Math., 11 (1963), 431-441. doi: 10.1137/0111030.
[15]	J. J. Moré, The Levenberg-Marquardt algorithm: implementation and theory, In: G. A. Watson, ed., Lecture Notes in Mathematics 630: Numerical Analysis, Springer-Verlag, Berlin, 1978, 105–116.
[16]	M. J. D. Powell, Convergence properties of a class of minimization algorithms, Nonlinear Programming, 2 (1974), 1-27.
[17]	G. W. Stewart and J.-G. Sun, Matrix Perturbation Theory, (Computer Science and Scientific Computing), Academic Press Boston, 1990.
[18]	H. Y. Wang and J. Y. Fan, Convergence rate of the Levenberg-Marquardt method under hölderian local error bound, Optimization Methods and Software, 2019. doi: 10.1080/10556788.2019.1694927.
[19]	N. Yamashita and M. Fukushima, On the rate of convergence of the Levenberg-Marquardt method, Computing, (15) (2001), 239-249. doi: 10.1007/978-3-7091-6217-0_18.
[20]	Y. X. Yuan, Recent advances in trust region algorithms, Math. Program., Ser. B, 151 (2015), 249–281. doi: 10.1007/s10107-015-0893-2.
[21]	X. D. Zhu and G. H. Lin, Improved convergence results for a modified Levenberg-Marquardt method for nonlinear equations and applications in MPCC, Optimization Methods and Software, 31 (2016), 791-804. doi: 10.1080/10556788.2016.1171863.