DocumentCode :
1903641
Title :
A GAOC Method for Topology Optimization Design
Author :
Chen, Zhimin ; Gao, Liang ; Qiu, Haobo ; Shao, Xinyu
Author_Institution :
State Key Lab. of Digital Manuf. Equip. & Technol., Huazhong Univ. of Sci. & Technol., Wuhan, China
Volume :
3
fYear :
2009
fDate :
10-11 Oct. 2009
Firstpage :
293
Lastpage :
296
Abstract :
This paper presents a new topology optimization method using hybrid genetic algorithm, namely GAOC, using the evolutionary mechanism of the genetic algorithm (GA) and the interpolation scheme of optimality criteria method (OC). In GAOC, the optimality criteria method is used to initialize the genetic population, and GA is then applied to the global search in the fixed design domain. In so doing the GAOC method can fully take advantage of the optimality criteria method and the genetic algorithm. The effectiveness of the GAOC method is demonstrated by the widely studied structural minimum weight design. Numerical examples show that the proposed optimization method GAOC can solve general topology optimization problems more effectively and can achieve better results with lower computational cost.
Keywords :
genetic algorithms; interpolation; search problems; structural engineering; topology; GAOC method; evolutionary mechanism; genetic population; global search; hybrid genetic algorithm; interpolation scheme; optimality criteria method; structural minimum weight design; structural topology optimization design; Algorithm design and analysis; Computer aided manufacturing; Design automation; Design optimization; Encoding; Genetic algorithms; Manufacturing automation; Optimization methods; Stochastic processes; Topology; Topology optimization; genetic algorithm (GA); minimum weight design; optimality criteria method (OC);
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Computation Technology and Automation, 2009. ICICTA '09. Second International Conference on
Conference_Location :
Changsha, Hunan
Print_ISBN :
978-0-7695-3804-4
Type :
conf
DOI :
10.1109/ICICTA.2009.537
Filename :
5287962
Link To Document :
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