A Newton-Like Trust Region Method for Large-Scale Unconstrained Nonconvex Minimization
Joint Authors
Chenhui, Zhang
Yueting, Yang
Weiwei, Yang
Mingyuan, Cao
Source
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-6, 6 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-10-21
Country of Publication
Egypt
No. of Pages
6
Main Subjects
Abstract EN
We present a new Newton-like method for large-scale unconstrained nonconvex minimization.
And a new straightforward limited memory quasi-Newton updating based on the modified quasi-Newton equation is deduced to construct the trust region subproblem, in which the information of both the function value and gradient is used to construct approximate Hessian.
The global convergence of the algorithm is proved.
Numerical results indicate that the proposed method is competitive and efficient on some classical large-scale nonconvex test problems.
American Psychological Association (APA)
Weiwei, Yang& Yueting, Yang& Chenhui, Zhang& Mingyuan, Cao. 2013. A Newton-Like Trust Region Method for Large-Scale Unconstrained Nonconvex Minimization. Abstract and Applied Analysis،Vol. 2013, no. 2013, pp.1-6.
https://search.emarefa.net/detail/BIM-474717
Modern Language Association (MLA)
Weiwei, Yang…[et al.]. A Newton-Like Trust Region Method for Large-Scale Unconstrained Nonconvex Minimization. Abstract and Applied Analysis No. 2013 (2013), pp.1-6.
https://search.emarefa.net/detail/BIM-474717
American Medical Association (AMA)
Weiwei, Yang& Yueting, Yang& Chenhui, Zhang& Mingyuan, Cao. A Newton-Like Trust Region Method for Large-Scale Unconstrained Nonconvex Minimization. Abstract and Applied Analysis. 2013. Vol. 2013, no. 2013, pp.1-6.
https://search.emarefa.net/detail/BIM-474717
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-474717