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On-line Access: 2024-08-27
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Optimal design of pressure vessel using an improved genetic algorithm
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Peng-fei LIU, Ping XU, Shu-xin HAN, Jin-yang ZHENG. Optimal design of pressure vessel using an improved genetic algorithm[J]. Journal of Zhejiang University Science A, 2008, 9(9): 1264-1269.
@article{title="Optimal design of pressure vessel using an improved genetic algorithm",
author="Peng-fei LIU, Ping XU, Shu-xin HAN, Jin-yang ZHENG",
journal="Journal of Zhejiang University Science A",
volume="9",
number="9",
pages="1264-1269",
year="2008",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.A0820217"
}
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%T Optimal design of pressure vessel using an improved genetic algorithm
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%A Ping XU
%A Shu-xin HAN
%A Jin-yang ZHENG
%J Journal of Zhejiang University SCIENCE A
%V 9
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%@ 1673-565X
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%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.A0820217
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T1 - Optimal design of pressure vessel using an improved genetic algorithm
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A1 - Ping XU
A1 - Shu-xin HAN
A1 - Jin-yang ZHENG
J0 - Journal of Zhejiang University Science A
VL - 9
IS - 9
SP - 1264
EP - 1269
%@ 1673-565X
Y1 - 2008
PB - Zhejiang University Press & Springer
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DOI - 10.1631/jzus.A0820217
Abstract: As the idea of simulated annealing (SA) is introduced into the fitness function, an improved genetic algorithm (GA) is proposed to perform the optimal design of a pressure vessel which aims to attain the minimum weight under burst pressure constraint. The actual burst pressure is calculated using the arc-length and restart analysis in finite element analysis (FEA). A penalty function in the fitness function is proposed to deal with the constrained problem. The effects of the population size and the number of generations in the GA on the weight and burst pressure of the vessel are explored. The optimization results using the proposed GA are also compared with those using the simple GA and the conventional Monte Carlo method.
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