APPLICATION OF HYBRID GENETIC ALGORITHM TO OPTIMUM DESIGN OF ENGINEERING STRUCTURES

Zhang Yannian; Liu Bin

doi:10.13204/j.gyjz200503010

Volume 35 Issue 3

Dec. 2014

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Article Navigation > INDUSTRIAL CONSTRUCTION > 2005 > 35(3): 23-26

HUANG Min, DUAN Jingmin, MAO Qingchao, WANG Jiakai. SEISMIC DYNAMIC RESPONSE ANALYSIS OF TWIN TUNNELS WITH DIFFERENT LINING STIFFNESS IN MOUNTAINS[J]. INDUSTRIAL CONSTRUCTION, 2021, 51(7): 39-46,63. doi: 10.13204/j.gyjzG21040603

Citation:

Zhang Yannian, Liu Bin, . APPLICATION OF HYBRID GENETIC ALGORITHM TO OPTIMUM DESIGN OF ENGINEERING STRUCTURES[J]. INDUSTRIAL CONSTRUCTION, 2005, 35(3): 23-26. doi: 10.13204/j.gyjz200503010

Citation:

Zhang Yannian, Liu Bin, . APPLICATION OF HYBRID GENETIC ALGORITHM TO OPTIMUM DESIGN OF ENGINEERING STRUCTURES[J]. INDUSTRIAL CONSTRUCTION, 2005, 35(3): 23-26. doi: 10.13204/j.gyjz200503010

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APPLICATION OF HYBRID GENETIC ALGORITHM TO OPTIMUM DESIGN OF ENGINEERING STRUCTURES

doi: 10.13204/j.gyjz200503010

Zhang Yannian¹,
Liu Bin¹,

1.
1. School of Resource and Civil Engineering,Northeastern University Shenyang 110004;
2.
2. Department of Civil Engineering,Liaoning Institute of Technology Jinzhou 121001

Received Date: 2004-08-25
Publish Date: 2005-03-20

Abstract

Abstract

On the basis of the practical structure design of engineering,sufficiently considering the constraint conditions that the norm stipulates and the requirements of various engineering standards,a model of building structural optimization is derived.A hybrid genetic algorithm(HGA)composed of the standard genetic algorithm(SGA)and the Fibonacci algorithm(FA)is proposed.The results of examples show that the method plays the advantages of saving time,high efficiency,powerful local searching capabilit of FA,and plays the advantages of global searching capability of genetic algorithm(GA),too.HGA,as an efficient optimization design method for engineering structure having the advantages of both FA and GA without their disadvantages,is superior to either one.
- discrete variables,
- structural optimization,
- genetic algorithm,
- hybrid genetic algorithm

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References(8)

References

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