Multi-objective anti-optimization analysis of structures with genetic algorithm

被引:0
|
作者
Zhao, XD [1 ]
Zhang, JH [1 ]
Zhang, J [1 ]
机构
[1] Xian Jiaotong Univ, State Key Lab Mech Struct Strenght & Vibrat, Xian 710049, Peoples R China
关键词
D O I
暂无
中图分类号
TH7 [仪器、仪表];
学科分类号
0804 ; 080401 ; 081102 ;
摘要
In structure analysis we just consider either the maximum force acts in structure or the maximum displacement that structure happens, but it is not determined now that which one is the much adverse factor to make structure fail. While either the maximum force is much bigger or the maximum displacement excesses the allowed value, the structure will be fail. In the other hand, earthquake excitation includes two factors: the earth ground acceleration and the field frequency. If earth ground acceleration is big enough, the structure will suffer big force, while the structure's nature frequency is much close to the frequency of field, the worse response will happen. Genetic Algorithm (GA) is a kind of parallel search algorithm, so that it can be used in multi-objective optimization problem. In this paper the two factors are considered together, here the objective function includes: the ground acceleration and the field predominant period, the constrain condition includes: the maximum structural base shear and the maximum structural displacement. The genetic algorithm is used to search the worst earthquake excitation that acts in structures. The excitation includes the ground acceleration and the field's period that cause the structure happens the maximum shear, and the maximum displacement.
引用
收藏
页码:4919 / 4921
页数:3
相关论文
共 50 条
  • [1] Hybrid Multi-Objective Genetic Algorithm for Multi-Objective Optimization Problems
    Zhang, Song
    Wang, Hongfeng
    Yang, Di
    Huang, Min
    [J]. 2015 27TH CHINESE CONTROL AND DECISION CONFERENCE (CCDC), 2015, : 1970 - 1974
  • [2] Multi-objective optimization of membrane structures based on Pareto Genetic Algorithm
    伞冰冰
    孙晓颖
    武岳
    [J]. Journal of Harbin Institute of Technology, 2010, 17 (05) : 622 - 630
  • [3] Multi-objective optimization of membrane structures based on Pareto Genetic Algorithm
    San, Bing-Bing
    Sun, Xiao-Ying
    Wu, Yue
    [J]. Journal of Harbin Institute of Technology (New Series), 2010, 17 (05) : 622 - 630
  • [4] Multi-objective optimization of membrane structures based on Pareto Genetic Algorithm
    伞冰冰
    孙晓颖
    武岳
    [J]. Journal of Harbin Institute of Technology(New series), 2010, (05) : 622 - 630
  • [5] A genetic algorithm for unconstrained multi-objective optimization
    Long, Qiang
    Wu, Changzhi
    Huang, Tingwen
    Wang, Xiangyu
    [J]. SWARM AND EVOLUTIONARY COMPUTATION, 2015, 22 : 1 - 14
  • [6] Genetic algorithm for multi-objective experimental optimization
    Link, Hannes
    Weuster-Botz, Dirk
    [J]. BIOPROCESS AND BIOSYSTEMS ENGINEERING, 2006, 29 (5-6) : 385 - 390
  • [7] A Parallel Genetic Algorithm in Multi-objective Optimization
    Wang Zhi-xin
    Ju Gang
    [J]. CCDC 2009: 21ST CHINESE CONTROL AND DECISION CONFERENCE, VOLS 1-6, PROCEEDINGS, 2009, : 3497 - 3501
  • [8] Genetic algorithm for multi-objective experimental optimization
    Hannes Link
    Dirk Weuster-Botz
    [J]. Bioprocess and Biosystems Engineering, 2006, 29 : 385 - 390
  • [9] Multi-objective optimization with improved genetic algorithm
    Ishibashi, H
    Aguirre, HE
    Tanaka, K
    Sugimura, T
    [J]. SMC 2000 CONFERENCE PROCEEDINGS: 2000 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN & CYBERNETICS, VOL 1-5, 2000, : 3852 - 3857
  • [10] An improved genetic algorithm for multi-objective optimization
    Lin, F
    He, GM
    [J]. PDCAT 2005: Sixth International Conference on Parallel and Distributed Computing, Applications and Technologies, Proceedings, 2005, : 938 - 940