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Sufficient Descent Conjugate Gradient Methods for Solving Convex Constrained Nonlinear Monotone Equations

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  • San-Yang Liu
  • Yuan-Yuan Huang
  • Hong-Wei Jiao

Abstract

Two unified frameworks of some sufficient descent conjugate gradient methods are considered. Combined with the hyperplane projection method of Solodov and Svaiter, they are extended to solve convex constrained nonlinear monotone equations. Their global convergence is proven under some mild conditions. Numerical results illustrate that these methods are efficient and can be applied to solve large-scale nonsmooth equations.

Suggested Citation

  • San-Yang Liu & Yuan-Yuan Huang & Hong-Wei Jiao, 2014. "Sufficient Descent Conjugate Gradient Methods for Solving Convex Constrained Nonlinear Monotone Equations," Abstract and Applied Analysis, Hindawi, vol. 2014, pages 1-12, January.
    • Handle: RePEc:hin:jnlaaa:305643
    DOI: 10.1155/2014/305643
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    Cited by:

    1. Najib Ullah & Abdullah Shah & Jamilu Sabi’u & Xiangmin Jiao & Aliyu Muhammed Awwal & Nuttapol Pakkaranang & Said Karim Shah & Bancha Panyanak, 2023. "A One-Parameter Memoryless DFP Algorithm for Solving System of Monotone Nonlinear Equations with Application in Image Processing," Mathematics, MDPI, vol. 11(5), pages 1-26, March.

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