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A New Hybrid Algorithm for Convex Nonlinear Unconstrained Optimization
Joint Authors
Ahmed, Huda I.
Al-Bayati, Abbas Y.
Hamed, Eman T.
Source
Journal of Applied Mathematics
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-6, 6 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-04-01
Country of Publication
Egypt
No. of Pages
6
Main Subjects
Abstract EN
In this study, we tend to propose a replacement hybrid algorithmic rule which mixes the search directions like Steepest Descent (SD) and Quasi-Newton (QN).
First, we tend to develop a replacement search direction for combined conjugate gradient (CG) and QN strategies.
Second, we tend to depict a replacement positive CG methodology that possesses the adequate descent property with sturdy Wolfe line search.
We tend to conjointly prove a replacement theorem to make sure global convergence property is underneath some given conditions.
Our numerical results show that the new algorithmic rule is powerful as compared to different standard high scale CG strategies.
American Psychological Association (APA)
Hamed, Eman T.& Ahmed, Huda I.& Al-Bayati, Abbas Y.. 2019. A New Hybrid Algorithm for Convex Nonlinear Unconstrained Optimization. Journal of Applied Mathematics،Vol. 2019, no. 2019, pp.1-6.
https://search.emarefa.net/detail/BIM-1168947
Modern Language Association (MLA)
Hamed, Eman T.…[et al.]. A New Hybrid Algorithm for Convex Nonlinear Unconstrained Optimization. Journal of Applied Mathematics No. 2019 (2019), pp.1-6.
https://search.emarefa.net/detail/BIM-1168947
American Medical Association (AMA)
Hamed, Eman T.& Ahmed, Huda I.& Al-Bayati, Abbas Y.. A New Hybrid Algorithm for Convex Nonlinear Unconstrained Optimization. Journal of Applied Mathematics. 2019. Vol. 2019, no. 2019, pp.1-6.
https://search.emarefa.net/detail/BIM-1168947
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1168947