![](/images/graphics-bg.png)
A Stochastic Trust Region Method for Unconstrained Optimization Problems
Joint Authors
Sun, Wenyu
Li, Ningning
Xue, Dan
Wang, Jing
Source
Mathematical Problems in Engineering
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-02-03
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
In this paper, a stochastic trust region method is proposed to solve unconstrained minimization problems with stochastic objectives.
Particularly, this method can be used to deal with nonconvex problems.
At each iteration, we construct a quadratic model of the objective function.
In the model, stochastic gradient is used to take the place of deterministic gradient for both the determination of descent directions and the approximation of the Hessians of the objective function.
The behavior and the convergence properties of the proposed method are discussed under some reasonable conditions.
Some preliminary numerical results show that our method is potentially efficient.
American Psychological Association (APA)
Li, Ningning& Xue, Dan& Sun, Wenyu& Wang, Jing. 2019. A Stochastic Trust Region Method for Unconstrained Optimization Problems. Mathematical Problems in Engineering،Vol. 2019, no. 2019, pp.1-10.
https://search.emarefa.net/detail/BIM-1197350
Modern Language Association (MLA)
Li, Ningning…[et al.]. A Stochastic Trust Region Method for Unconstrained Optimization Problems. Mathematical Problems in Engineering No. 2019 (2019), pp.1-10.
https://search.emarefa.net/detail/BIM-1197350
American Medical Association (AMA)
Li, Ningning& Xue, Dan& Sun, Wenyu& Wang, Jing. A Stochastic Trust Region Method for Unconstrained Optimization Problems. Mathematical Problems in Engineering. 2019. Vol. 2019, no. 2019, pp.1-10.
https://search.emarefa.net/detail/BIM-1197350
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1197350