Modifying Of Barzilai and Borwein Method for Solving Large-Scale Unconstrained Optimization Problems. [PDF]
المجلة العراقية للعلوم الاحصائية, 2007 In this paper we present a technique for computing the minimum value of an objective function in the frame of gradient descent methods based on combination of Barzilai and Borwein approximation of Hessian matrix of objective function and Lipchetz ...
Khalil K. Abbo
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Complexity bounds for second-order optimality in unconstrained optimization [PDF]
Journal of Complexity, 2011 AbstractThis paper examines worst-case evaluation bounds for finding weak minimizers in unconstrained optimization. For the cubic regularization algorithm, Nesterov and Polyak (2006) [15] and Cartis et al. (2010) [3] show that at most O(ϵ−3) iterations may have to be performed for finding an iterate which is within ϵ of satisfying second-order ...
Coralia Cartis +2 more
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The Diagonal Update for Unconstrained Optimization [PDF]
مجلة التربية والعلم, 2012 In this research we introduced a new update of the Hessian matrix or we updating only the diagonal elements of Hessian matrix, and make the non-diagonal elements always equal to zero and in this case we can preserve the sparse property so called the ...
Saad Shakir Mahmood +2 more
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A spectral Fletcher-Reeves conjugate gradient method with integrated strategy for unconstrained optimization and portfolio selection. [PDF]
PLoS ONEThe spectral conjugate gradient (SCG) technique is highly efficient in addressing large-scale unconstrained optimization challenges. This paper presents a structured SCG approach that combines the Quasi-Newton direction and an extended conjugacy ...
Nasiru Salihu +4 more
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Unconstrained Optimization with MINTOOLKIT for GNU Octave [PDF]
, 2004 The paper documents MINTOOLKIT for GNU Octave. MINTOOLKIT provides functions for minimization and numeric differentiation. The main algorithms are BFGS, LBFGS, and simulated annealing.
Michael Creel
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Spectral proximal method for solving large scale sparse optimization [PDF]
ITM Web of Conferences, 2021 In this paper, we propose to use spectral proximal method to solve sparse optimization problems. Sparse optimization refers to an optimization problem involving the ι0 -norm in objective or constraints.
Woo Gillian Yi Han +3 more
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On the hardness of quadratic unconstrained binary optimization problems
Frontiers in Physics, 2022 We use exact enumeration to characterize the solutions of quadratic unconstrained binary optimization problems of less than 21 variables in terms of their distributions of Hamming distances to close-by solutions.
V. Mehta +7 more
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A Sufficient Descent Property for a Different Parameter to Enhance Three-Term Method [PDF]
Al-Rafidain Journal of Computer Sciences and Mathematics, 2023 In this paper, we derive a new parameter µk-1 for the three-term CG (N3T) algorithm for solving unconstrained optimization problems. As demonstrated by its calculations and proof, the parameter µk-1 worth is determined by T , and the study ...
Ghada Al-Naemi, Samaa Al-bakri
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A Combined Cubic and Novel Line Search CG-Algorithm [PDF]
Al-Rafidain Journal of Computer Sciences and Mathematics, 2012 In this paper a new line search technique is investigated. It uses (cubic and novel) line searches in the standard CG-algorithm for unconstrained optimization.
Abbas Al-Bayati, Hamsa Chilmerane
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A Modified Genetic Algorithm in C++ for Optimization of Steel Truss Structures [PDF]
Journal of Soft Computing in Civil Engineering, 2021 A common structural design optimization problem is weight minimization which is done by choosing a set of variables that represent the structural or the architectural configuration of the system satisfying few design specific criterion.
Pawan Kumar +2 more
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