A Conjugate Gradient Method Based on a Modified Secant Relation for Unconstrained Optimization. (3rd April 2020)

• Record Type: Journal Article
• Authors: Dehghani, Razieh; Bidabadi, Narges; Fahs, Hassan; Hosseini, Mohammad Mehdi
• Is Part Of: Numerical functional analysis and optimization. Volume 41:Number 5(2020)
• Page Start: 621
• Page End: 634
• Publication Date: 2020-04-03
• Subjects: Conjugate gradient method -- global convergence -- secant relation -- unconstrained optimization; 90C30 -- 90C53 -- 49M37 -- 65K05; Functional analysis -- Periodicals; Numerical analysis -- Periodicals; Mathematical optimization -- Periodicals; Numerical Analysis, Computer-Assisted; 515.705
• DOI: 10.1080/01630563.2019.1669641
• Languages: English
• ISSNs: 0163-0563

Abstract

Abstract: Based on the modified secant relation given by Zhang and Xu and making use of the Dai and Liao approach, Babaie-Kafaki et al. presented a conjugate gradient method to solve unconstrained optimization. In this paper, we made some modifications on the conjugate gradient parameter proposed by Babaie-Kafaki et al. and obtained some attractive results in theory and practice. Under appropriate conditions, we show that the proposed method is globally convergent without needing convexity assumption on the objective function. Comparative results show computational efficiency of the proposed method in the sense of the Dolan-Moré performance profiles.