The Hybrid BFGS-CG Method in Solving Unconstrained Optimization Problems. (4th March 2014)

• Record Type: Journal Article
• Authors: Ibrahim, Mohd Asrul Hery; Mamat, Mustafa; Leong, Wah June
• Other Names: Jodar Lucas Academic Editor.
• Is Part Of: Abstract and applied analysis. Volume 2014(2014)
• Publication Date: 2014-03-04
• Subjects: Mathematical analysis -- Periodicals; Mathematical analysis; Applied Mathematics; Mathematical Analysis; Periodicals; 515.05
• DOI: 10.1155/2014/507102
• Languages: English
• ISSNs: 1085-3375

Abstract

Abstract : In solving large scale problems, the quasi-Newton method is known as the most efficient method in solving unconstrained optimization problems. Hence, a new hybrid method, known as the BFGS-CG method, has been created based on these properties, combining the search direction between conjugate gradient methods and quasi-Newton methods. In comparison to standard BFGS methods and conjugate gradient methods, the BFGS-CG method shows significant improvement in the total number of iterations and CPU time required to solve large scale unconstrained optimization problems. We also prove that the hybrid method is globally convergent.