Skip to main content
Top
Published in: Numerical Algorithms 4/2020

15-05-2019 | Original Paper

A derivative-free conjugate residual method using secant condition for general large-scale nonlinear equations

Author: Li Zhang

Published in: Numerical Algorithms | Issue 4/2020

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

A fully derivative-free conjugate residual method, using secant condition, is introduced to solve general large-scale nonlinear equations. Under some conditions, global and linear convergence of the proposed method is established by adopting some backtracking type line search. Some numerical results compared with two existing derivative-free methods are reported to show its efficiency.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Literature
1.
go back to reference Yuan, Y.: Recent advances in numerical methods for nonlinear equations and nonlinear least squares. Numer. Alge. Cont. Optim. 1, 15–34 (2011)MathSciNetCrossRef Yuan, Y.: Recent advances in numerical methods for nonlinear equations and nonlinear least squares. Numer. Alge. Cont. Optim. 1, 15–34 (2011)MathSciNetCrossRef
2.
go back to reference Li, D., Fukushima, M.: A globally and superlinearly convergent Gauss-Newton-based BFGS method for symmetric nonlinear equations. SIAM J. Numer. Anal. 37, 152–172 (1999)MathSciNetCrossRef Li, D., Fukushima, M.: A globally and superlinearly convergent Gauss-Newton-based BFGS method for symmetric nonlinear equations. SIAM J. Numer. Anal. 37, 152–172 (1999)MathSciNetCrossRef
3.
go back to reference Zhou, W.: A Gauss-Newton-based BFGS method for symmetric nonlinear least squares problems. Pacific J. Optim. 9, 373–389 (2013)MathSciNetMATH Zhou, W.: A Gauss-Newton-based BFGS method for symmetric nonlinear least squares problems. Pacific J. Optim. 9, 373–389 (2013)MathSciNetMATH
4.
go back to reference Zhou, W., Chen, X.: Global convergence of a new hybrid Gauss-Newton structured BFGS methods for nonlinear least squares problems. SIAM J. Optim. 20, 2422–2441 (2010)MathSciNetCrossRef Zhou, W., Chen, X.: Global convergence of a new hybrid Gauss-Newton structured BFGS methods for nonlinear least squares problems. SIAM J. Optim. 20, 2422–2441 (2010)MathSciNetCrossRef
5.
go back to reference Yamashita, N., Fukushima, M.: On the rate of convergence of the Levenberg-Marquardt method. Computing (Supp.) 15, 237–249 (2001)MathSciNetMATH Yamashita, N., Fukushima, M.: On the rate of convergence of the Levenberg-Marquardt method. Computing (Supp.) 15, 237–249 (2001)MathSciNetMATH
6.
go back to reference Li, Q., Li, D.: A class of derivative-free methods for large-scale nonlinear monotone equations. IMA J. Numer. Anal. 31, 1625–1635 (2011)MathSciNetCrossRef Li, Q., Li, D.: A class of derivative-free methods for large-scale nonlinear monotone equations. IMA J. Numer. Anal. 31, 1625–1635 (2011)MathSciNetCrossRef
7.
go back to reference Zhou, W., Shen, D.: Convergence properties of an iterative method for solving symmetric nonlinear equations. J. Optim. Theory Appl. 164, 277–289 (2015)MathSciNetCrossRef Zhou, W., Shen, D.: Convergence properties of an iterative method for solving symmetric nonlinear equations. J. Optim. Theory Appl. 164, 277–289 (2015)MathSciNetCrossRef
8.
go back to reference Zhou, W., Shen, D.: An inexact PRP conjugate gradient method for symmetric nonlinear equations. Numer. Funct. Anal. Optim. 35, 370–388 (2014)MathSciNetCrossRef Zhou, W., Shen, D.: An inexact PRP conjugate gradient method for symmetric nonlinear equations. Numer. Funct. Anal. Optim. 35, 370–388 (2014)MathSciNetCrossRef
9.
go back to reference Zhou, W., Wang, F.: A PRP-based residual method for large-scale monotone nonlinear equations. Appl. Math. Comput. 261, 1–7 (2015)MathSciNetMATH Zhou, W., Wang, F.: A PRP-based residual method for large-scale monotone nonlinear equations. Appl. Math. Comput. 261, 1–7 (2015)MathSciNetMATH
10.
go back to reference Zhou, W., Li, D.: On the Q-linear convergence rate of a class of methods for monotone nonlinear equations. Pacific J. Optim. 14, 723–737 (2018)MathSciNet Zhou, W., Li, D.: On the Q-linear convergence rate of a class of methods for monotone nonlinear equations. Pacific J. Optim. 14, 723–737 (2018)MathSciNet
11.
go back to reference La Cruz, W., Raydan, M.: Nonmonotone spectral methods for large-scale nonlinear systems. Optim. Methods Softw. 18, 583–599 (2003)MathSciNetCrossRef La Cruz, W., Raydan, M.: Nonmonotone spectral methods for large-scale nonlinear systems. Optim. Methods Softw. 18, 583–599 (2003)MathSciNetCrossRef
12.
go back to reference La Cruz, W., Martinez, J.M., Raydan, M.: Spectral residual method without gradient information for solving large-scale nonlinear systems of equations. Math. Comput. 75, 1429–1448 (2006)MathSciNetCrossRef La Cruz, W., Martinez, J.M., Raydan, M.: Spectral residual method without gradient information for solving large-scale nonlinear systems of equations. Math. Comput. 75, 1429–1448 (2006)MathSciNetCrossRef
13.
go back to reference Cheng, W., Xiao, Y., Hu, Q.: A family of derivative-free conjugate gradient methods for large-scale nonlinear systems of equations. J. Comput. Appl. Math. 224, 11–19 (2009)MathSciNetCrossRef Cheng, W., Xiao, Y., Hu, Q.: A family of derivative-free conjugate gradient methods for large-scale nonlinear systems of equations. J. Comput. Appl. Math. 224, 11–19 (2009)MathSciNetCrossRef
14.
go back to reference Dai, Y., Liao, L.: New conjugacy conditions and related nonlinear conjugate gradient methods. Appl. Math. Optim. 43, 87–101 (2001)MathSciNetCrossRef Dai, Y., Liao, L.: New conjugacy conditions and related nonlinear conjugate gradient methods. Appl. Math. Optim. 43, 87–101 (2001)MathSciNetCrossRef
15.
go back to reference Polak, E., Ribière, G.: Note sur la convergence de méthodes de directions conjuguées. Rev. Fr. Inform. Rech. Oper. 16, 35–43 (1969)MATH Polak, E., Ribière, G.: Note sur la convergence de méthodes de directions conjuguées. Rev. Fr. Inform. Rech. Oper. 16, 35–43 (1969)MATH
16.
go back to reference Polyak, B.T.: The conjugate gradient method in extreme problems. USSR Comput. Math. Math. Phys. 9, 94–112 (1969)CrossRef Polyak, B.T.: The conjugate gradient method in extreme problems. USSR Comput. Math. Math. Phys. 9, 94–112 (1969)CrossRef
17.
go back to reference Hestenes, M.R., Stiefel, E.L.: Methods of conjugate gradients for solving linear systems. J. Res. Nat. Bur. Standards 49, 409–436 (1952)MathSciNetCrossRef Hestenes, M.R., Stiefel, E.L.: Methods of conjugate gradients for solving linear systems. J. Res. Nat. Bur. Standards 49, 409–436 (1952)MathSciNetCrossRef
18.
go back to reference Grippo, L., Lucidi, S.: A globally convergent version of the Polak-Ribière conjugate gradient method. Math. Program. 78, 375–391 (1997)MATH Grippo, L., Lucidi, S.: A globally convergent version of the Polak-Ribière conjugate gradient method. Math. Program. 78, 375–391 (1997)MATH
19.
go back to reference Dai, Y.: Conjugate gradient methods with Armijo-type line searches. Acta Math. Appl. Sin. -Engl. Ser. 18, 123–130 (2002)MathSciNetCrossRef Dai, Y.: Conjugate gradient methods with Armijo-type line searches. Acta Math. Appl. Sin. -Engl. Ser. 18, 123–130 (2002)MathSciNetCrossRef
20.
21.
go back to reference Zhou, W., Li, D.: On the convergence properties of the unmodified PRP method with a non-descent line search. Optim. Methods Softw. 29, 484–496 (2014)MathSciNetCrossRef Zhou, W., Li, D.: On the convergence properties of the unmodified PRP method with a non-descent line search. Optim. Methods Softw. 29, 484–496 (2014)MathSciNetCrossRef
22.
go back to reference Dai, Y.: Nonlinear Conjugate Gradient Methods. Wiley Encyclopedia of Operations Research and Management Science (2011) Dai, Y.: Nonlinear Conjugate Gradient Methods. Wiley Encyclopedia of Operations Research and Management Science (2011)
23.
go back to reference Dennis, J.E., Moré, J.J.: A characterization of superlinear convergence and its applications to quasi-Newton methods. Math. Comput. 28, 549–560 (1974)MathSciNetCrossRef Dennis, J.E., Moré, J.J.: A characterization of superlinear convergence and its applications to quasi-Newton methods. Math. Comput. 28, 549–560 (1974)MathSciNetCrossRef
24.
go back to reference Dolan, E.D., Moré, J.J.: Benchmarking optimization software with performance profiles. Math. Program. 91, 201–213 (2002)MathSciNetCrossRef Dolan, E.D., Moré, J.J.: Benchmarking optimization software with performance profiles. Math. Program. 91, 201–213 (2002)MathSciNetCrossRef
Metadata
Title
A derivative-free conjugate residual method using secant condition for general large-scale nonlinear equations
Author
Li Zhang
Publication date
15-05-2019
Publisher
Springer US
Published in
Numerical Algorithms / Issue 4/2020
Print ISSN: 1017-1398
Electronic ISSN: 1572-9265
DOI
https://doi.org/10.1007/s11075-019-00725-7

Other articles of this Issue 4/2020

Numerical Algorithms 4/2020 Go to the issue

Premium Partner