Skip to main content
Log in

Two modified three-term conjugate gradient methods with sufficient descent property

  • Original Paper
  • Published:
Optimization Letters Aims and scope Submit manuscript

Abstract

Based on the insight gained from the three-term conjugate gradient methods suggested by Zhang et al. (Optim Methods Softw 22:697–711, 2007) two nonlinear conjugate gradient methods are proposed, making modifications on the conjugate gradient methods proposed by Dai and Liao (Appl Math Optim 43:87–101, 2001), and Zhou and Zhang (Optim Methods Softw 21:707–714, 2006). The methods can be regarded as modified versions of two three-term conjugate gradient methods proposed by Sugiki et al. (J Optim Theory Appl 153:733–757, 2012) in which the search directions are computed using the secant equations in a way to achieve the sufficient descent property. One of the methods is shown to be globally convergent for uniformly convex objective functions while the other is shown to be globally convergent without convexity assumption on the objective function. Comparative numerical results demonstrating efficiency of the proposed methods are reported.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

References

  1. Andrei, N.: Numerical comparison of conjugate gradient algorithms for unconstrained optimization. Stud. Inform. Control 16(4), 333–352 (2007)

    MathSciNet  Google Scholar 

  2. Andrei, N.: Another hybrid conjugate gradient algorithm for unconstrained optimization. Numer. Algorithms 47(2), 143–156 (2008)

    Article  MATH  MathSciNet  Google Scholar 

  3. Andrei, N.: Open problems in conjugate gradient algorithms for unconstrained optimization. B. Malays. Math. Sci. So. 34(2), 319–330 (2011)

    MATH  MathSciNet  Google Scholar 

  4. Babaie-Kafaki, S., Ghanbari, R., Mahdavi-Amiri, N.: Two new conjugate gradient methods based on modified secant equations. J. Comput. Appl. Math. 234(5), 1374–1386 (2010)

    Article  MATH  MathSciNet  Google Scholar 

  5. Dai, Y.H., Liao, L.Z.: New conjugacy conditions and related nonlinear conjugate gradient methods. Appl. Math. Optim. 43(1), 87–101 (2001)

    Article  MATH  MathSciNet  Google Scholar 

  6. Dolan, E.D., More, J.J.: Benchmarking optimization software with performance profiles. Math. Program. 91(2 Ser. A), 201–213 (2002)

    Article  MATH  MathSciNet  Google Scholar 

  7. Du, D., Pardalos, P.M., Wu, W.: Mathematical Theory of Optimization. Kluwer Academic Publishers, Dordrecht (2001)

    Book  MATH  Google Scholar 

  8. Gould, N.I.M., Orban, D., Toint, PhL: CUTEr: a constrained and unconstrained testing environment, revisited. ACM Trans. Math. Softw. 29(4), 373–394 (2003)

    Article  MATH  MathSciNet  Google Scholar 

  9. Hager, W.W., Zhang, H.: Algorithm 851: CG\_Descent, a conjugate gradient method with guaranteed descent. ACM Trans. Math. Softw. 32(1), 113–137 (2006)

    Article  MathSciNet  Google Scholar 

  10. Hager, W.W., Zhang, H.: A survey of nonlinear conjugate gradient methods. Pac. J. Optim. 2(1), 35–58 (2006)

    MATH  MathSciNet  Google Scholar 

  11. Hestenes, M.R., Stiefel, E.: Methods of conjugate gradients for solving linear systems. J. Res. Nat. Bur. Stands. 49(6), 409–436 (1952)

    Article  MATH  MathSciNet  Google Scholar 

  12. Li, D.H., Fukushima, M.: A modified BFGS method and its global convergence in nonconvex minimization. J. Comput. Appl. Math. 129(1–2), 15–35 (2001)

    Article  MATH  MathSciNet  Google Scholar 

  13. Sugiki, K., Narushima, Y., Yabe, H.: Globally convergent three-term conjugate gradient methods that use secant conditions and generate descent search directions for unconstrained optimization. J. Optim. Theory Appl. 153(3), 733–757 (2012)

    Article  MATH  MathSciNet  Google Scholar 

  14. Sun, W., Yuan, Y.X.: Optimization Theory and Methods: Nonlinear Programming. Springer, New York (2006)

    Google Scholar 

  15. Zhang, L., Zhou, W., Li, D.H.: Some descent three-term conjugate gradient methods and their global convergence. Optim. Methods Softw. 22(4), 697–711 (2007)

    Article  MathSciNet  Google Scholar 

  16. Zhou, W., Zhang, L.: A nonlinear conjugate gradient method based on the MBFGS secant condition. Optim. Methods Softw. 21(5), 707–714 (2006)

    Article  MATH  MathSciNet  Google Scholar 

Download references

Acknowledgments

This research was supported by Research Councils of Semnan University and Ferdowsi University of Mashhad. The authors are grateful to Professor William W. Hager for providing the CG_Descent code. They also thank the anonymous referees for their valuable suggestions helped to improve the quality of this work.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Saman Babaie-Kafaki.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Babaie-Kafaki, S., Ghanbari, R. Two modified three-term conjugate gradient methods with sufficient descent property. Optim Lett 8, 2285–2297 (2014). https://doi.org/10.1007/s11590-014-0736-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11590-014-0736-8

Keywords

Navigation