A New Three-Term Conjugate Gradient Method for Unconstrained Optimization with Applications in Portfolio Selection and Robotic Motion Control

Maulana Malik*, Auwal Bala Abubakar, Ibrahim Mohammed Sulaiman, Mustafa Mamat, Siti Sabariah Abas, Sukono

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Three-term conjugate gradient method is one of the efficient method for solving unconstrained optimization models. In this paper, we propose a new three-term conjugate gradient method with a new search direction structure. A remarkable feature of the proposed method is that independent of the line search procedure, the search direction always satisfies the sufficient descent condition. The global convergence properties of the proposed method is established under the strong Wolfe line search by assuming that the objective function is Lipschitz continuous. Numerical results indicate that our proposed method is efficient and robust, thus effective in solving unconstrained optimization models. In addition, the proposed method also considered practical application problem in portfolio selection and robotic motion control.

Original languageEnglish
Pages (from-to)1-16
Number of pages16
JournalIAENG International Journal of Applied Mathematics
Volume51
Issue number3
Publication statusPublished - 2021
Externally publishedYes

Keywords

  • global convergence properties
  • motion control
  • portfolio selection
  • sufficient descent condition
  • Three-term conjugate gradient method
  • unconstrained optimization

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