Paper Info
Title
A bit-array representation GA for structural topology optimization
Abstract
A bit-array representation method for structural topology optimization using the GA is proposed. The importance of design connectivity is further emphasized and a hierarchical violation penalty method is proposed to penalize the violated constraint functions so that the problem of representation degeneracy can be overcome and the GA search can be driven towards the combination of better structural performance, less unusable material and fewer connected objects in the design domain. An identical initialization method is also proposed to test the performance of the GA operators. With the appropriately selected GA operators, the bit-array representation GA is applied to the structural topology optimization problems of minimum weight. Numerical results demonstrate that the present GA can achieve better accuracy with less computational cost and suggest that the GA performance can be significantly improved by handling the design connectivity properly.
Year
DOI
Venue
2003
10.1109/CEC.2003.1299640
IEEE Congress on Evolutionary Computation (1)
Keywords
Field
DocType
computational cost,constraint function,hierarchical violation penalty,minimum weight design problem,numerical analysis,structural engineering computing,population initialization method,performance testing,bit-array representation ga,genetic algorithm,topology,genetic algorithms,structural topology optimization,design connectivity problem,representation degeneracy,connectivity analysis,penalty method,topology optimization
Mathematical optimization,Computer science,Degeneracy (mathematics),Artificial intelligence,Minimum weight,Topology optimization,Initialization,Bit array,Machine learning,Computational topology,Genetic algorithm,Penalty method
Conference
Volume
ISBN
Citations 
1
0-7803-7804-0
0
PageRank 
References 
Authors
0.34
2
2
Name
Order
Citations
PageRank
Sheng Yin Wang100.34
K. Tai217722.25