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Optimization
A Journal of Mathematical Programming and Operations Research
Volume 67, 2018 - Issue 10
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Articles

A family of quasi-Newton methods for unconstrained optimization problems

M. S. SalimDepartment of Mathematics, Faculty of Science, Al-Azhar University, Assiut, Egypt
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A. I. AhmedDepartment of Mathematics, Faculty of Science, Al-Azhar University, Assiut, EgyptCorrespondence[email protected] [email protected]
Pages 1717-1727 | Received 18 Sep 2017, Accepted 02 Jun 2018, Published online: 20 Jun 2018

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Read on this site (2)

A. I. Ahmed. (2022) A new filled function for global minimization and system of nonlinear equations. Optimization 71:14, pages 4083-4106.
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A. I. Ahmed. (2021) A new parameter free filled function for solving unconstrained global optimization problems. International Journal of Computer Mathematics 98:1, pages 106-119.
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Jamshaid Ul Rahman, Faiza Makhdoom, Akhtar Ali & Sana Danish. (2023) Mathematical modeling and simulation of biophysics systems using neural network. International Journal of Modern Physics B 38:05.
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Xiangjuan Wu, Yuping Wang & Ninglei Fan. (2021) A new filled function method based on adaptive search direction and valley widening for global optimization. Applied Intelligence 51:8, pages 6234-6254.
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E. Lavasa, G. Giannopoulos, A. Papaioannou, A. Anastasiadis, I. A. Daglis, A. Aran, D. Pacheco & B. Sanahuja. (2021) Assessing the Predictability of Solar Energetic Particles with the Use of Machine Learning Techniques. Solar Physics 296:7.
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Pengyuan Li, Zhan Wang, Dan Luo & Hongtruong Pham. (2020) Global Convergence of a Modified Two-Parameter Scaled BFGS Method with Yuan-Wei-Lu Line Search for Unconstrained Optimization. Mathematical Problems in Engineering 2020, pages 1-15.
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M.S. Salim & A.I. Ahmed. (2018) A quasi-Newton augmented Lagrangian algorithm for constrained optimization problems. Journal of Intelligent & Fuzzy Systems 35:2, pages 2373-2382.
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