Open AccessNew Hybrid Conjugate Gradient Method with Global Convergence Properties under Exact Line Search
Author(s) -
Yasir Salih,
Mustafa Mamat,
Mohd Rivaie,
Abdelrhaman Abashar,
Mohamad Afendee Mohamed
Publication year - 2018
Publication title -
international journal of engineering and technology
Language(s) - English
Resource type - Journals
ISSN - 2227-524X
DOI - 10.14419/ijet.v7i3.28.20965
Subject(s) - conjugate gradient method , nonlinear conjugate gradient method , line search , convergence (economics) , mathematics , gradient descent , derivation of the conjugate gradient method , descent (aeronautics) , gradient method , mathematical optimization , conjugate residual method , conjugate , line (geometry) , nonlinear system , scale (ratio) , representation (politics) , computer science , mathematical analysis , artificial neural network , physics , geometry , artificial intelligence , computer security , law , economic growth , quantum mechanics , political science , radius , politics , meteorology , economics
Conjugate Gradient (CG) method is a very useful technique for solving large-scale nonlinear optimization problems. In this paper, we propose a new formula for 12خ²k"> , which is a hybrid of PRP and WYL methods. This method possesses sufficient descent and global convergence properties when used with exact line search. Numerical results indicate that the new formula has higher efficiency compared with other classical CG methods.