Results 1 to 10 of about 820,651 (313)
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 modified Liu-Storey scheme for nonlinear systems with an application to image recovery [PDF]
Iranian Journal of Numerical Analysis and Optimization, 2023 Like the Polak-Ribi`ere-Polyak (PRP) and Hestenes-Stiefel (HS) meth-ods, the classical Liu-Storey (LS) conjugate gradient scheme is widely be-lieved to perform well numerically.
A.I. Kiri, M.Y. Waziri, K. Ahmed
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Journal of Numerical Analysis and Approximation Theory, 2020 This paper presents a comparative numerical study between line search methods and majorant functions to compute the displacement step in barrier logarithmic method for linear programming.
Soraya Chaghoub, Djamel Benterki
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An adaptive descent extension of the Polak–Rebière–Polyak conjugate gradient method based on the concept of maximum magnification [PDF]
Iranian Journal of Numerical Analysis and Optimization, 2021 Recently, a one-parameter extension of the Polak–Rebière–Polyak method has been suggested, having acceptable theoretical features and promising numerical behavior.
Z. Aminifard, S. Babaie-Kafaki
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Logarithmic Barrier Method Via Minorant Function for Linear Semidefinite Programming
Annales Mathematicae Silesianae, 2023 We propose in this study, a new logarithmic barrier approach to solve linear semidefinite programming problem. We are interested in computation of the direction by Newton’s method and of the displacement step using minorant functions instead of line ...
Leulmi Assma
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Mathematics, 2022 In this paper, a hybrid gradient simulated annealing algorithm is guided to solve the constrained optimization problem. In trying to solve constrained optimization problems using deterministic, stochastic optimization methods or hybridization between ...
Khalid Abdulaziz Alnowibet +4 more
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A New hybrid generalized CG- method for non-linear functions [PDF]
Al-Rafidain Journal of Computer Sciences and Mathematics, 2010 In this paper a new extended generalized conjugate gradient algorithm is proposed for unconstrained optimization, which is considered as anew inverse hyperbolic model .In order to improve the rate of convergence of the new technique, a new hybrid ...
Abbas Al-Bayati, Hamsa Chilmerane
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An Accelerated Convex Optimization Algorithm with Line Search and Applications in Machine Learning
Mathematics, 2022 In this paper, we introduce a new line search technique, then employ it to construct a novel accelerated forward–backward algorithm for solving convex minimization problems of the form of the summation of two convex functions in which one of these ...
Dawan Chumpungam +2 more
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A Novel Forward-Backward Algorithm for Solving Convex Minimization Problem in Hilbert Spaces
Mathematics, 2020 In this work, we aim to investigate the convex minimization problem of the sum of two objective functions. This optimization problem includes, in particular, image reconstruction and signal recovery.
Suthep Suantai +2 more
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A New Hybrid Approach for Solving Large-scale Monotone Nonlinear Equations
Journal of Mathematical and Fundamental Sciences, 2020 In this paper, a new hybrid conjugate gradient method for solving monotone nonlinear equations is introduced. The scheme is a combination of the Fletcher-Reeves (FR) and Polak-Ribiére-Polyak (PRP) conjugate gradient methods with the Solodov and Svaiter ...
Jamilu Sabi’u +3 more
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