Global convergence of Hager–Zhang type Riemannian conjugate gradient method

Hiroyuki Sakai, Hiroyuki Sato and Hideaki Iiduka

Applied Mathematics and Computation, 2023, vol. 441, issue C

Abstract: This paper presents the Hager–Zhang (HZ)-type Riemannian conjugate gradient method that uses the exponential retraction. We also present global convergence analyses of our proposed method under two kinds of assumptions. Moreover, we numerically compare our proposed methods with the existing methods by solving two kinds of Riemannian optimization problems on the unit sphere. The numerical results show that our proposed method has much better performance than the existing methods, i.e., the FR, DY, PRP, and HS methods. In particular, they show that it has much higher performance than existing methods including the hybrid ones in computing the stability number of graphs problem.

Keywords: Riemannian optimization; Riemannian manifold; Conjugate gradient method; Hager–Zhang method (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:apmaco:v:441:y:2023:i:c:s0096300322007536

DOI: 10.1016/j.amc.2022.127685

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