On the usefulness of non-gradient approaches in topology optimization

被引:340
作者
Sigmund, Ole [1 ]
机构
[1] Tech Univ Denmark, Dept Mech Engn, DK-2800 Lyngby, Denmark
关键词
Topology optimization; Genetic Algorithms; Stochastic optimization; Discrete optimization; COMPLIANT MECHANISMS; GENETIC ALGORITHM; DESIGN;
D O I
10.1007/s00158-011-0638-7
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Topology optimization is a highly developed tool for structural design and is by now being extensively used in mechanical, automotive and aerospace industries throughout the world. Gradient-based topology optimization algorithms may efficiently solve fine-resolution problems with thousands and up to millions of design variables using a few hundred (finite element) function evaluations (and even less than 50 in some commercial codes). Nevertheless, non-gradient topology optimization approaches that require orders of magnitude more function evaluations for extremely low resolution examples keep appearing in the literature. This forum article discusses the practical and scientific relevance of publishing papers that use immense computational resources for solving simple problems for which there already exist efficient solution techniques.
引用
收藏
页码:589 / 596
页数:8
相关论文
共 55 条
[1]   GA topology optimization using random keys for tree encoding of structures [J].
Aguilar Madeira, J. F. ;
Pina, H. L. ;
Rodrigues, H. C. .
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION, 2010, 40 (1-6) :227-240
[2]   Structural optimization using sensitivity analysis and a level-set method [J].
Allaire, G ;
Jouve, F ;
Toader, AM .
JOURNAL OF COMPUTATIONAL PHYSICS, 2004, 194 (01) :363-393
[3]   Efficient topology optimization in MATLAB using 88 lines of code [J].
Andreassen, Erik ;
Clausen, Anders ;
Schevenels, Mattias ;
Lazarov, Boyan S. ;
Sigmund, Ole .
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION, 2011, 43 (01) :1-16
[4]   Performance evaluation of a two stage adaptive genetic algorithm (TSAGA) in structural topology optimization [J].
Balamurugan, R. ;
Ramakrishnan, C. V. ;
Singh, Nidur .
APPLIED SOFT COMPUTING, 2008, 8 (04) :1607-1624
[5]   A two phase approach based on skeleton convergence and geometric variables for topology optimization using genetic algorithm [J].
Balamurugan, R. ;
Ramakrishnan, C. V. ;
Swaminathan, N. .
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION, 2011, 43 (03) :381-404
[6]  
Bendose M.P., 2004, Topology Optimization: Theory, Methods and Applications, V2nd
[7]  
Bendsoe M. P., 1989, Struct. Optim., V1, P193, DOI [10.1007/BF01650949, DOI 10.1007/BF01650949]
[8]   GENERATING OPTIMAL TOPOLOGIES IN STRUCTURAL DESIGN USING A HOMOGENIZATION METHOD [J].
BENDSOE, MP ;
KIKUCHI, N .
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING, 1988, 71 (02) :197-224
[9]   Toward the topology design of mechanisms that exhibit snap-through behavior [J].
Bruns, TE ;
Sigmund, O .
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING, 2004, 193 (36-38) :3973-4000
[10]   Maximizing band gaps in two-dimensional photonic crystals [J].
Cox, SJ ;
Dobson, DC .
SIAM JOURNAL ON APPLIED MATHEMATICS, 1999, 59 (06) :2108-2120