A deep neural network-based algorithm for solving structural optimization
Abstract
We propose the deep Lagrange method (DLM), which is a new optimization method, in this study. It is based on a deep neural network to solve optimization problems. The method takes the advantage of deep learning artificial neural networks to find the optimal values of the optimization function instead of solving optimization problems by calculating sensitivity analysis. The DLM method is non-linear and could potentially deal with nonlinear optimization problems. Several test cases on sizing optimization and shape optimization are performed, and their results are then compared with analytical and numerical solutions.
Details
- Organisation(s)
-
Institute of Photonics
Hannover Centre for Optical Technologies (HOT)
- External Organisation(s)
-
Tongji University
- Type
- Article
- Journal
- Journal of Zhejiang University: Science A
- Volume
- 22
- Pages
- 609-620
- No. of pages
- 12
- ISSN
- 1673-565X
- Publication date
- 08.2021
- Publication status
- Published
- Peer reviewed
- Yes
- ASJC Scopus subject areas
- General Engineering
- Electronic version(s)
-
https://doi.org/10.1631/jzus.A2000380 (Access:
Closed
)
-
Details in the research portal "Research@Leibniz University"
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