求解无约束优化问题的分式模型信赖域算法
A trust region method based on the fractional model for unconstrained optimization
Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review
Author(s)
Detail(s)
| Original language | Chinese (Simplified) |
|---|---|
| Pages (from-to) | 531-546 |
| Journal / Publication | 中国科学:数学 |
| Volume | 48 |
| Issue number | 4 |
| Online published | 19 Mar 2018 |
| Publication status | Published - Apr 2018 |
Link(s)
| DOI | DOI |
|---|---|
| Permanent Link | https://scholars.cityu.edu.hk/en/publications/publication(2ae9ecc5-7901-428f-820c-24239fa7c802).html |
Abstract
本文提出一个求解无约束优化问题的分式模型信赖域拟Newton算法.在新算法中,分式模型信赖域子问题是用简单折线法求解的.在合理假设条件下,算法的全局收敛性获得了证明.数值实验结果表明新算法是可行、有效的.
In this paper, we propose a new quasi-Newton method based on a fractional model for solving unconstrained optimization problems. In the new method, a generalized dogleg algorithm is established for solving the subproblem with a fractional model. We prove the global convergence of the proposed algorithm. Numerical experiment shows the feasibility and validity of the new quasi-Newton method.
Research Area(s)
- 无约束优化, 分式模型, 信赖域算法, 拟 Newton 算法, 全局收敛性, unconstrained optimization, fractional model, trust region method, quasi-Newton method, global convergence
