Convergence Analysis of an Improved BFGS Method and Its Application in the Muskingum Model
Joint Authors
Wang, Xiaoliang
Yang, Tianshan
Li, Pengyuan
Source
Mathematical Problems in Engineering
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-08-18
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
The BFGS method is one of the most effective quasi-Newton algorithms for minimization-optimization problems.
In this paper, an improved BFGS method with a modified weak Wolfe–Powell line search technique is used to solve convex minimization problems and its convergence analysis is established.
Seventy-four academic test problems and the Muskingum model are implemented in the numerical experiment.
The numerical results show that our algorithm is comparable to the usual BFGS algorithm in terms of the number of iterations and the time consumed, which indicates our algorithm is effective and reliable.
American Psychological Association (APA)
Yang, Tianshan& Li, Pengyuan& Wang, Xiaoliang. 2020. Convergence Analysis of an Improved BFGS Method and Its Application in the Muskingum Model. Mathematical Problems in Engineering،Vol. 2020, no. 2020, pp.1-9.
https://search.emarefa.net/detail/BIM-1195224
Modern Language Association (MLA)
Yang, Tianshan…[et al.]. Convergence Analysis of an Improved BFGS Method and Its Application in the Muskingum Model. Mathematical Problems in Engineering No. 2020 (2020), pp.1-9.
https://search.emarefa.net/detail/BIM-1195224
American Medical Association (AMA)
Yang, Tianshan& Li, Pengyuan& Wang, Xiaoliang. Convergence Analysis of an Improved BFGS Method and Its Application in the Muskingum Model. Mathematical Problems in Engineering. 2020. Vol. 2020, no. 2020, pp.1-9.
https://search.emarefa.net/detail/BIM-1195224
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1195224