An efficient hybrid conjugate gradient method with the strong Wolfe-Powell line search

Conjugate gradient (CG) method is an interesting tool to solve optimization problems in many fields, such as design, economics, physics, and engineering. In this paper, we depict a new hybrid of CG method which relates to the famous Polak-Ribiere-Polyak ` (PRP) formula. It reveals a solution for the...

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Bibliographic Details
Main Authors: Mustafa, Mamat, Ahmad, Alhawarat, Mohd, Rivaie
Format: Article
Language:English
English
Published: Hindawi Publishing Corporation 2015
Subjects:
Online Access:http://eprints.unisza.edu.my/6582/1/FH02-FIK-15-03719.jpg
http://eprints.unisza.edu.my/6582/2/FH02-FIK-15-03770.jpg
http://eprints.unisza.edu.my/6582/
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Institution: Universiti Sultan Zainal Abidin
Language: English
English
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Summary:Conjugate gradient (CG) method is an interesting tool to solve optimization problems in many fields, such as design, economics, physics, and engineering. In this paper, we depict a new hybrid of CG method which relates to the famous Polak-Ribiere-Polyak ` (PRP) formula. It reveals a solution for the PRP case which is not globally convergent with the strong Wolfe-Powell (SWP) line search. The new formula possesses the sufficient descent condition and the global convergent properties. In addition, we further explained about the cases where PRP method failed with SWP line search. Furthermore, we provide numerical computations for the new hybrid CG method which is almost better than other related PRP formulas in both the number of iterations and the CPU time under some standard test functions.