Global convergence of the Polak-Ribière-Polyak conjugate gradient method with an Armijo-type inexact line search for nonconvex unconstrained optimization problems

Zeng Xin Wei, Guo Yin Li, Liqun Qi

Research output: Journal article publicationJournal articleAcademic researchpeer-review

42 Citations (Scopus)

Abstract

We propose two algorithms for nonconvox unconstrained optimization problems that employ Polak-Ribicro-Polyak conjugate gradient formula and new inexact line search techniques. We show that the new algorithms converge globally if the function to be minimized has Lipschitz continuous gradients. Preliminary numerical results show that the proposed methods for particularly chosen line search conditions are very promising.
Original languageEnglish
Pages (from-to)2173-2193
Number of pages21
JournalMathematics of Computation
Volume77
Issue number264
DOIs
Publication statusPublished - 1 Oct 2008

Keywords

  • Global convergence
  • Inexact line search
  • Nonconvex optimization
  • PRP method

ASJC Scopus subject areas

  • Algebra and Number Theory
  • Computational Mathematics
  • Applied Mathematics

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