Solving Large-Scale Unconstrained Optimization Problems with an Efficient Conjugate Gradient Class
The main goal of this paper is to introduce an appropriate conjugate gradient class to solve unconstrained optimization problems. The presented class enjoys the benefits of having three free parameters, its directions are descent, and it can fulfill the Dai–Liao conjugacy condition. Global convergen...
Saved in:
Main Authors: | Sanaz Bojari, Mahmoud Paripour |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2024-01-01
|
Series: | Journal of Mathematics |
Online Access: | http://dx.doi.org/10.1155/2024/5548724 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
An Efficient Modified AZPRP Conjugate Gradient Method for Large-Scale Unconstrained Optimization Problem
by: Ahmad Alhawarat, et al.
Published: (2021-01-01) -
A Conjugate Gradient Method with Global Convergence for Large-Scale Unconstrained Optimization Problems
by: Shengwei Yao, et al.
Published: (2013-01-01) -
A Conjugate Gradient Method for Unconstrained Optimization Problems
by: Gonglin Yuan
Published: (2009-01-01) -
A Modified Hybrid Conjugate Gradient Method for Unconstrained Optimization
by: Minglei Fang, et al.
Published: (2021-01-01) -
Several Guaranteed Descent Conjugate Gradient Methods for Unconstrained Optimization
by: San-Yang Liu, et al.
Published: (2014-01-01)