Applying the Powell's Symmetrical Technique to Conjugate Gradient Methods with the Generalized Conjugacy Condition. (2nd July 2016)

• Record Type: Journal Article
• Authors: Benrabia, Noureddine; Laskri, Yamina; Guebbai, Hamza; Al-Baali, Mehiddin
• Is Part Of: Numerical functional analysis and optimization. Volume 37:Number 7(2016)
• Page Start: 839
• Page End: 849
• Publication Date: 2016-07-02
• Subjects: Conjugate gradient method -- generalized conjugacy condition -- global convergence -- spectral analysis -- symmetrical technique; 49M37 -- 49M05 -- 49M30 -- 90C06 -- 90C30; Functional analysis -- Periodicals; Numerical analysis -- Periodicals; Mathematical optimization -- Periodicals; Numerical Analysis, Computer-Assisted; 515.705
• DOI: 10.1080/01630563.2016.1178142
• Languages: English
• ISSNs: 0163-0563

Abstract

ABSTRACT: This article proposes new conjugate gradient method for unconstrained optimization by applying the Powell symmetrical technique in a defined sense. Using the Wolfe line search conditions, the global convergence property of the method is also obtained based on the spectral analysis of the conjugate gradient iteration matrix and the Zoutendijk condition for steepest descent methods. Preliminary numerical results for a set of 86 unconstrained optimization test problems verify the performance of the algorithm and show that the Generalized Descent Symmetrical Hestenes-Stiefel algorithm is competitive with the Fletcher-Reeves (FR) and Polak-Ribiére-Polyak ( PRP + ) algorithms.