A Modified Spectral Conjugate Gradient Method with Global Convergence

  • Parvaneh Faramarzi
  • Keyvan AminiEmail author


In this paper, a modified version of the spectral conjugate gradient algorithm suggested by Jian, Chen, Jiang, Zeng and Yin is proposed. It is proved that the new method is globally convergent for general nonlinear functions, under some standard assumptions. Based on the modified secant condition and quasi-Newton directions, some new spectral parameters are introduced. It is shown that the search direction satisfies the sufficient descent property independent of the line search. Numerical experiments indicate a promising behavior of the new algorithm, especially for large-scale problems.


Global convergence Sufficient descent property Unconstrained optimization Spectral conjugate gradient Modified secant condition 

Mathematics Subject Classification

90C30 65K05 



The authors are grateful to the anonymous referees and editor for suggestions and comments during the preparation of the paper.


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© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Mathematics, Faculty of ScienceRazi UniversityKermanshahIran

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