Global convergence of the Armijo epsilon steepest descent algorithm

Authors

  • Nour E. Rahali Souk Ahras University, Algeria
  • Nacera Djeghaba Badji Mokhtar University, Algeria
  • Rachid Benzine Badji Mokhtar University, Algeria

DOI:

https://doi.org/10.33993/jnaat412-978

Keywords:

unconstrained optimization, global convergence, steepest descent algorithm, \( \varepsilon\)-algorithm, Armijo inexact line search
Abstract views: 298

Abstract

In this article, we study the unconstrained minimization problem\[(P)\,\,\,\min\left\{ f(x):x\in\mathbb{R}^{n}\right\} .\]where \(f:\mathbb{R}^{n}\rightarrow\mathbb{R}\) is a continuously differentiable function. We introduce a new algorithm which accelerates the convergence of the steepest descent method. We further establish the global convergence of this algorithm in the case of Armijo inexact line search.

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References

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Published

2012-08-01

How to Cite

Rahali, N. E., Djeghaba, N., & Benzine, R. (2012). Global convergence of the Armijo epsilon steepest descent algorithm. Rev. Anal. Numér. Théor. Approx., 41(2), 169–180. https://doi.org/10.33993/jnaat412-978

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