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A modified Wei–Yao–Liu conjugate gradient method for unconstrained optimization

Authors
Journal
Applied Mathematics and Computation
0096-3003
Publisher
Elsevier
Publication Date
Volume
231
Identifiers
DOI: 10.1016/j.amc.2014.01.012
Keywords
  • Unconstrained Optimization
  • Conjugate Gradient Method
  • Sufficient Descent Condition
  • Global Convergence

Abstract

Abstract In this paper, we give a modified Wei–Yao–Liu conjugate gradient method (Wei et al., 2006 [18]), which will reduce to the original Wei–Yao–Liu method, and possess the sufficient descent property without any line search. Furthermore, we prove that the presented method is globally convergent for nonconvex functions with the weak Wolfe–Powell line search. In a similar way, we also extend these results to the modified Liu–Storey method. Preliminary numerical results show that the proposed methods are effective for the given test problems.

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