.png){kind=icon}
返回
On D-optimality based trust regions for black-box optimization problems
.png){kind=icon}
OA
AI
DOI：10.1007/s00158-005-0541-1.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Various sequential derivative-free optimization algorithms exist for solving black-box optimization problems. Two important building blocks in these algorithms are the trust region and the geometry improvement. In this paper, we propose to incorporate the D-optimality criterion, well known in the design of experiments, into these algorithms in two different ways. Firstly, it is used to define a trust region that adapts its shape to the locations of the points in which the objective function has been evaluated. Secondly, it is used to determine an optimal geometry-improving point. The proposed trust region and geometry improvement can both be implemented into existing sequential algorithms.
Keyword:
D-optimality
trust region
derivative-free
optimization
affine transformations
geometry
期刊
IF:
4
论文数:
4.9K
被引数:
1.7W
机构
暂无机构信息
引用论文
Virological suppression does not prevent the development of hepatocellular carcinoma in HBeAg-negative chronic hepatitis B patients with cirrhosis receiving oral antiviral(s) starting with lamivudine monotherapy: results of the nationwide HEPNET. Greece cohort study.png)
Gut
GutIF0
PREAI
分享收藏 没有更多内容
没有更多内容