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New version of the three-term conjugate gradient method based on spectral scaling conjugacy condition that generates descent search direction

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  • Dong, Xiao Liang
  • Liu, Hong Wei
  • He, Yu Bo

Abstract

In this paper, a general form of three-term conjugate gradient method is presented, in which the search directions simultaneously satisfy the Dai–Liao conjugacy condition and sufficient descent property. In addition, the choice for an optimal parameter is suggested in the sense that the condition number of the iteration matrix could arrives at its minimum, which can be regarded as the inheritance and development of the spectral scaling quasi-Newton equation. Different from the existent methods, a new update strategy in constructing the search direction is proposed to establish the global convergence for the general function. Numerical results show our algorithm is practical and effective for the test problems.

Suggested Citation

  • Dong, Xiao Liang & Liu, Hong Wei & He, Yu Bo, 2015. "New version of the three-term conjugate gradient method based on spectral scaling conjugacy condition that generates descent search direction," Applied Mathematics and Computation, Elsevier, vol. 269(C), pages 606-617.
    • Handle: RePEc:eee:apmaco:v:269:y:2015:i:c:p:606-617
    DOI: 10.1016/j.amc.2015.07.067
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    References listed on IDEAS

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    1. Kaori Sugiki & Yasushi Narushima & Hiroshi Yabe, 2012. "Globally Convergent Three-Term Conjugate Gradient Methods that Use Secant Conditions and Generate Descent Search Directions for Unconstrained Optimization," Journal of Optimization Theory and Applications, Springer, vol. 153(3), pages 733-757, June.
    2. Wanyou Cheng & Donghui Li, 2012. "An Active Set Modified Polak–Ribiére–Polyak Method for Large-Scale Nonlinear Bound Constrained Optimization," Journal of Optimization Theory and Applications, Springer, vol. 155(3), pages 1084-1094, December.
    3. Babaie-Kafaki, Saman & Ghanbari, Reza, 2014. "The Dai–Liao nonlinear conjugate gradient method with optimal parameter choices," European Journal of Operational Research, Elsevier, vol. 234(3), pages 625-630.
    4. Neculai Andrei, 2013. "Another Conjugate Gradient Algorithm with Guaranteed Descent and Conjugacy Conditions for Large-scale Unconstrained Optimization," Journal of Optimization Theory and Applications, Springer, vol. 159(1), pages 159-182, October.
    5. XiaoLiang Dong & Hongwei Liu & Yubo He, 2015. "A Self-Adjusting Conjugate Gradient Method with Sufficient Descent Condition and Conjugacy Condition," Journal of Optimization Theory and Applications, Springer, vol. 165(1), pages 225-241, April.
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    Cited by:

    1. XiaoLiang Dong & Deren Han & Zhifeng Dai & Lixiang Li & Jianguang Zhu, 2018. "An Accelerated Three-Term Conjugate Gradient Method with Sufficient Descent Condition and Conjugacy Condition," Journal of Optimization Theory and Applications, Springer, vol. 179(3), pages 944-961, December.

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