Title :
Genetic algorithms for optimal design of underground reinforced concrete tube structure
Author :
Zhao, Sheng-Li ; Li, Min-qiang ; Kou, Ji-Song ; Liu, Yan
Author_Institution :
Sch. of Manage., Tianjin Univ., China
Abstract :
Applying genetic algorithms to optimal design of underground reinforced concrete tube structure, the author develops the optimal model of structural design based on genetic algorithms for underground reinforced concrete tube. An example of the reinforced concrete tube structure is calculated by the proposed computer programs based on genetic algorithms optimal model, and the result indicates that using genetic algorithms for optimizing the design of underground reinforced concrete tube structure can reduce the engineering cost in a large degree, and also guarantee the safety of structure. Therefore, this method is feasible and effective.
Keywords :
concrete; construction components; design for quality; genetic algorithms; structural engineering; genetic algorithms optimal model; structural design; underground reinforced concrete tube structure; Agricultural engineering; Algorithm design and analysis; Biological cells; Concrete; Cost function; Design engineering; Design optimization; Genetic algorithms; Genetic mutations; Safety;
Conference_Titel :
Machine Learning and Cybernetics, 2004. Proceedings of 2004 International Conference on
Print_ISBN :
0-7803-8403-2
DOI :
10.1109/ICMLC.2004.1382184
