Open AccessNew Conjugate Gradient Method Addressing Large Scale Unconstrained Optimization Problem
Author(s) -
Mohd Yusof,
Mohd Asrul,
Hasherah Mohd Ibrahim,
Mohd Rivaei,
Mustafa Mamat,
Mohamad Afendee,
Liza Puspa
Publication year - 2019
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.l1133.10812s219
Subject(s) - conjugate gradient method , derivation of the conjugate gradient method , convergence (economics) , nonlinear conjugate gradient method , conjugate residual method , line search , gradient method , mathematical proof , mathematical optimization , computer science , scale (ratio) , mathematics , algorithm , gradient descent , artificial intelligence , geometry , physics , radius , computer security , quantum mechanics , artificial neural network , economics , economic growth
An iterative conjugate gradient (CG) method is prominently known for dealing with unconstrained optimization problem. A new CG method which is modified by Wei Yao Liu (WYL) method is tested by standard test functions. Moreover, the step size is calculated using exact line search. Theoretical proofs on convergence analysis are shown. As a result, this new CG is comparable to the other methods in finding the optimal points by measuring the total iterations required as well as the computing time. Numerical results showed the execution between three CG methods in details.