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A Conjugate Gradient Algorithm under Yuan-Wei-Lu Line Search Technique for Large-Scale Minimization Optimization Models

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  • Xiangrong Li
  • Songhua Wang
  • Zhongzhou Jin
  • Hongtruong Pham

Abstract

This paper gives a modified Hestenes and Stiefel (HS) conjugate gradient algorithm under the Yuan-Wei-Lu inexact line search technique for large-scale unconstrained optimization problems, where the proposed algorithm has the following properties: the new search direction possesses not only a sufficient descent property but also a trust region feature; the presented algorithm has global convergence for nonconvex functions; the numerical experiment showed that the new algorithm is more effective than similar algorithms.

Suggested Citation

  • Xiangrong Li & Songhua Wang & Zhongzhou Jin & Hongtruong Pham, 2018. "A Conjugate Gradient Algorithm under Yuan-Wei-Lu Line Search Technique for Large-Scale Minimization Optimization Models," Mathematical Problems in Engineering, Hindawi, vol. 2018, pages 1-11, January.
    • Handle: RePEc:hin:jnlmpe:4729318
    DOI: 10.1155/2018/4729318
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