A modified Hestenes-Stiefel method for solving unconstrained optimization problems

Volume: 10, Issue: 5, Pages: 2126 - 2138
Published: Aug 21, 2020
Abstract
The conjugate gradient methods are among the most efficient methods for solving optimization models. This is due to its simplicity, low memory requirement and the properties of its global convergent. Many researchers try to improve this technique. In this paper, we suggested a modification of the conjugate gradient parameter with global convergence properties via exact minimization rule. Preliminary experiment was conducted using some...
Paper Details
Title
A modified Hestenes-Stiefel method for solving unconstrained optimization problems
Published Date
Aug 21, 2020
Volume
10
Issue
5
Pages
2126 - 2138
Citation AnalysisPro
  • Scinapse’s Top 10 Citation Journals & Affiliations graph reveals the quality and authenticity of citations received by a paper.
  • Discover whether citations have been inflated due to self-citations, or if citations include institutional bias.