.png){kind=icon}
返回
Automatic innovative truss design using grammatical evolution
.png){kind=icon}
PRE
AI
DOI：10.1016/j.autcon.2013.11.009.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Truss optirnization in the field of Structural Engineering is a growing discipline. The application of Grammatical Evolution, a grammar-based form of Genetic Programming (GP), has shown that it is capable of generating innovative engineering designs. Existing truss optimization methods in GP focus primarily on optimizing global topology. The standard method is to explore the search space while seeking minimum cross-sectional areas for all elements. In doing so, critical knowledge of section geometry and orientation is omitted, leading to inaccurate stress calculations and structures not meeting codes of practice. This can be addressed by constraining the optimisation method to only use standard construction elements. The aim of this paper is not to find fully optimized solutions, but rather to show that solutions very close to the theoretical optimum can be achieved using real-world elements. This methodology can be applied to any structural engineering design which can be generated by a grammar. (C) 2013 Elsevier B.V. All rights reserved.
Keyword:
Structural optimization
Genetic programming
Evolutionary computation
Grammatical evolution
Truss design
Computer aided design
期刊
IF:
11.5
论文数:
6.3K
被引数:
4.2W
机构
引用论文
.png){kind=icon}
Performance enhancement of multiobjective evolutionary optimisers for truss design using an approximate gradient使用近似梯度增强用于桁架设计的多目标进化优化器的性能
PREAI
分享收藏
查看更多内容