A scaled three-term conjugate gradient method for convex-constrained monotone nonlinear equations and application. Issue 1 (1st May 2022)

• Record Type: Journal Article
• Authors: Abdullahi, H; Awasthi, A K; Waziri, M Y; Halilu, A S
• Is Part Of: Journal of physics. Volume 2267:Issue 1(2022)
• Publication Date: 2022-05-01
• Subjects: Physics -- Congresses; 530.5
• DOI: 10.1088/1742-6596/2267/1/012066
• Languages: English
• ISSNs: 1742-6588

Abstract

Abstract: One of the fastest, old, and most adopted method for solving unconstrained optimization problems is the conjugate gradient method (cg). Over the decades, several types of research have been put in place to extend the methods (cg) to solving constrained monotone nonlinear equations. This paper presents a scaled three-term cg for convex-constrained monotone nonlinear equations. The proposed method fulfills descent (sufficient) property as well as trust-region feature. Two sets of numerical experiments were carried off and demonstrate the effectiveness of the proposed method by comparison with existing methods in the literature. In the first experiment, the proposed method was applied and solved some convex-constrained monotone nonlinear equations using some benchmark test functions. For the second experiment, a signal problem; that arose from compressed sensing was restored by applying the proposed method.