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Dai-Kou type conjugate gradient methods with a line search only using gradient [PDF]
Journal of Inequalities and Applications, 2017 In this paper, the Dai-Kou type conjugate gradient methods are developed to solve the optimality condition of an unconstrained optimization, they only utilize gradient information and have broader application scope.
Yuanyuan Huang, Changhe Liu
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A family of conjugate gradient methods for large-scale nonlinear equations [PDF]
Journal of Inequalities and Applications, 2017 In this paper, we present a family of conjugate gradient projection methods for solving large-scale nonlinear equations. At each iteration, it needs low storage and the subproblem can be easily solved.
Dexiang Feng, Min Sun, Xueyong Wang
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Preconditioned conjugate gradient methods for absolute value equations
Journal of Numerical Analysis and Approximation Theory, 2020 We investigate the NP-hard absolute value equations (AVE), \(Ax-B|x| =b\), where \(A,B\) are given symmetric matrices in \(\mathbb{R}^{n\times n}, \ b\in \mathbb{R}^{n}\).
Nassima Anane, Mohamed Achache
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A NEW THREE -TERM CONJUGATE GRADIENT ALGORITHM FOR SOLVING MINIMIZATION PROBLEMS
Science Journal of University of Zakho, 2023 The method of optimization is used to determine the most precise value for certain functions within a certain domain; it is mostly studied and employed in the fields of mathematics, computer science, and physics.
Dilovan H. Omar +2 more
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A Combined Conjugate Gradient Quasi-Newton Method with Modification BFGS Formula
International Journal of Analysis and Applications, 2023 The conjugate gradient and Quasi-Newton methods have advantages and drawbacks, as although quasi-Newton algorithm has more rapid convergence than conjugate gradient, they require more storage compared to conjugate gradient algorithms.
Mardeen Sh. Taher, Salah G. Shareef
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Development a Special Conjugate Gradient Algorithm for Solving Unconstrained Minimization Problems [PDF]
Al-Rafidain Journal of Computer Sciences and Mathematics, 2012 This paper develops a special conjugate gradient algorithm for solving unconstrained minimized problems. This development can be regarded as some kind of convex combination of the MPR and MLS methods.
Basim Hassan
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EURO Journal on Computational Optimization, 2022 Nonlinear conjugate gradients are among the most popular techniques for solving continuous optimization problems. Although these schemes have long been studied from a global convergence standpoint, their worst-case complexity properties have yet to be ...
Rémi Chan–Renous-Legoubin +1 more
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New conjugacy condition with pair-conjugate gradient methods for unconstrained optimization [PDF]
Al-Rafidain Journal of Computer Sciences and Mathematics, 2009 Conjugate gradient methods are wildly used for unconstrained optimization especially when the dimension is large. In this paper we propose a new kind of nonlinear conjugate gradient methods which on the study of Dai and Liao (2001), the new idea is how ...
Abbas Al-Bayati, Huda Ahmed
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Least-squares-based three-term conjugate gradient methods
Journal of Inequalities and Applications, 2020 In this paper, we first propose a new three-term conjugate gradient (CG) method, which is based on the least-squares technique, to determine the CG parameter, named LSTT.
Chunming Tang, Shuangyu Li, Zengru Cui
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A New Spectral Conjugate Gradient method for solving unconstrained Optimization problems [PDF]
مجلة ابحاث كلية التربية الاساسية, 2022 The spectral conjugate gradient methods are fascinating, and it has been shown that they are useful for strictly convex quadratic reduction when used properly.
أسامة محمد طاهر ویس +2 more
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