DocumentCode
517520
Title
Hybrid genetic algorithm and its application in structural optimization design
Author
Bai, Xinli ; Li, Yuhe ; Yang, Kaiyun
Author_Institution
North China Univ. of Water Resources & Electr. Power, Zhengzhou, China
fYear
2010
fDate
16-18 April 2010
Firstpage
415
Lastpage
417
Abstract
The principle of the simple genetic algorithm (SGA) is described in this paper. The SGA being taken as the global search method, and the traditional direct search method for mixed-discrete variables as the local search method, the hybrid genetic algorithm (HGA) is formed by improving the SGA. And through the introduction of penalty constraints, the problem dealing with the constraints in GA is successfully resolved. A mathematical model for structural optimization of aqueduct is established, and computer software is developed for structural optimization of large-scale aqueduct based on HGA, finally the optimal solution is obtained. As compared to the original design, the optimal design saves more than 20% of the engineering investment, and was adopted by Design Institute. The results show that the feasibility and effectiveness of the method is worth further popularization.
Keywords
canals; design engineering; genetic algorithms; search problems; structural engineering computing; aqueduct; computer software; direct search method; global search method; hybrid genetic algorithm; local search method; mathematical model; mixed-discrete variables; penalty constraints; simple genetic algorithm; structural optimization design; Algorithm design and analysis; Biological cells; Biological system modeling; Design engineering; Design optimization; Evolution (biology); Genetic algorithms; Mathematical model; Search methods; Water resources; Aqueduct; hybrid genetic algorithm (HGA); mixed-discrete variables; niche; structural optimization design;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Management and Engineering (ICIME), 2010 The 2nd IEEE International Conference on
Conference_Location
Chengdu
Print_ISBN
978-1-4244-5263-7
Electronic_ISBN
978-1-4244-5265-1
Type
conf
DOI
10.1109/ICIME.2010.5478094
Filename
5478094
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