Some New Scaled Conjugate Gradient Methods Via Symmetric Rank-One Update for Unconstrained Optimization

Basim A. Hassan*, Hawraz N. Jabbar, Fadhil Alfarag, Sunusi Bala Abdullahi, Abdulkarim Hassan Ibrahim

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This work demonstrates some of scaled conjugate gradient algorithms based on order-one symmetric modernization. We adopted the outstanding attributes of the symmetric rank-one update (SR1) in providing superiority Hessian approximations that lead the development of a conjugate gradient with descent property and having no resources for the matrices. The obtained numerical results depicted the superiority of the method.

Original languageEnglish
Title of host publicationProceedings of the 1st International Conference on Advanced Research in Pure and Applied Science, ICARPAS 2021
Subtitle of host publication3rd Annual Conference of Al-Muthanna University/College of Science
EditorsLaith Abdul Hassan M. Jawad, Firas Faeq K. Hussain, Ahmed Fadhil Almurshedi, Tammar Hussein Ali, Hana Kadum Al-Mussawi, Safaa Kareem Kadhem, Sadiq Majeed
PublisherAmerican Institute of Physics Inc.
ISBN (Electronic)9780735444010
DOIs
StatePublished - 25 Oct 2022
Externally publishedYes
Event1st International Conference on Advanced Research in Pure and Applied Science, ICARPAS 2021 - Al-Samawah, Iraq
Duration: 24 Mar 202125 Mar 2021

Publication series

NameAIP Conference Proceedings
Volume2398
ISSN (Print)0094-243X
ISSN (Electronic)1551-7616

Conference

Conference1st International Conference on Advanced Research in Pure and Applied Science, ICARPAS 2021
Country/TerritoryIraq
CityAl-Samawah
Period24/03/2125/03/21

Bibliographical note

Publisher Copyright:
© 2022 American Institute of Physics Inc.. All rights reserved.

Keywords

  • Conjugate gradient
  • Descent condition
  • Numerical results
  • Scaled conjugate gradient

ASJC Scopus subject areas

  • General Physics and Astronomy

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