Evolutionary structural optimisation (ESO) using a bidirectional algorithm

被引:479
|
作者
Querin, OM [1 ]
Steven, GP
Xie, YM
机构
[1] Univ Sydney, Dept Aeronaut Engn, Sydney, NSW 2006, Australia
[2] Victoria Univ Technol, Melbourne, Vic 3000, Australia
关键词
algorithms; structural optimisation;
D O I
10.1108/02644409810244129
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Describes development work to combine the basic ESO with the additive evolutionary structural optimisation (AESO) to produce bidirectional ESO whereby material can be added and can be removed. It will be shown that this provides the same results as the traditional ESO. This has two benefits, it validates the whole ESO concept and there is a significant time saving since the structure grows from a small initial one rather than contracting from a sometimes huge initial one where 90 per cent of the material gets removed over many hundreds of finite element analysis (FEA) evolutionary cycles. Presents a brief background to the current state of Structural Optimisation research. This is followed by a discussion of the strategies for the bidirectional ESO (BESO) algorithm and two examples are presented.
引用
收藏
页码:1031 / +
页数:19
相关论文
共 50 条
  • [31] Introduction of fixed grid in evolutionary structural optimisation
    Kim, H
    Garcia, MJ
    Querin, OM
    Steven, GP
    Xie, YM
    ENGINEERING COMPUTATIONS, 2000, 17 (04) : 427 - 439
  • [32] A Cellular Genetic Algorithm for Structural Optimisation
    Gholizadeh, S.
    Salajegheh, E.
    PROCEEDINGS OF THE TENTH INTERNATIONAL CONFERENCE ON COMPUTATIONAL STRUCTURES TECHNOLOGY, 2010, 93
  • [33] Bidirectional Dynamic Diversity Evolutionary Algorithm for Constrained Optimization
    Gao, Weishang
    Shao, Cheng
    An, Yi
    MATHEMATICAL PROBLEMS IN ENGINEERING, 2013, 2013
  • [34] An Exploration Of The Space Of DNA Structural Properties Using An Evolutionary Algorithm
    Ashlock, Wendy
    2016 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC), 2016, : 4713 - 4720
  • [35] Bidirectional Evolutionary Structural Optimization with Regional Penalty Factor
    Wang C.
    Zhang C.
    Liu T.
    Liao W.
    Zhang, Changdong (zcd@njust.edu.cn), 2018, Institute of Computing Technology (30): : 2224 - 2233
  • [36] Evolutionary algorithm for structural optimization
    Voss, MS
    Foley, CM
    GECCO-99: PROCEEDINGS OF THE GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE, 1999, : 678 - 685
  • [37] REACTIVE DISTILLATION FOR MULTIPLE-REACTION SYSTEMS: OPTIMISATION STUDY USING AN EVOLUTIONARY ALGORITHM
    Keller, Tobias
    Dreisewerd, Bjoern
    Gorak, Andrzej
    CHEMICAL AND PROCESS ENGINEERING-INZYNIERIA CHEMICZNA I PROCESOWA, 2013, 34 (01): : 17 - 38
  • [38] Model based optimisation of the design of a middle vessel batch distillation by using an evolutionary algorithm
    Leipold, M.
    Gruetzmann, S.
    Fieg, G.
    FORSCHUNG IM INGENIEURWESEN-ENGINEERING RESEARCH, 2009, 73 (03): : 161 - 172
  • [39] Structural Optimisation of a Suspension Control Arm Using a Bi-Evolutionary Bone Remodelling Inspired Algorithm and the Radial Point Interpolation Method
    Oliveira, Carlos
    Pais, Ana
    Belinha, Jorge
    APPLIED SCIENCES-BASEL, 2025, 15 (02):
  • [40] Crushing plant optimisation by means of a genetic evolutionary algorithm
    Svedensten, P
    Evertsson, CM
    MINERALS ENGINEERING, 2005, 18 (05) : 473 - 479