Kriging Approximation Method for Structural Optimization Using Genetic Algorithms
Date Issued
2008
Date
2008
Author(s)
Chen, Yung-Chih
Abstract
This thesis proposes the Kriging approximation method for structural optimization using genetic algorithms. Firstly, geometric parameters of a structure are defined, and a parametric design program is developed to automatically generate the solid model of the structure. Then, a macro program is developed to automatically analyze structural behaviors of the structure. In building the Kriging approximation model, some sample data points around the point of interest are selected, and exact fitness values of these data points are calculated from the analytical results for interpolating the Kriging model. In genetic algorithm processes, a modified trust region approach is proposed as evolution control. The fitness values of all individuals are evaluated exactly only for some specific generations. The fitness values of individuals for other generations are evaluated approximately by Kriging approximation model. Finally, an integrated program combining computer aided design software, finite element analysis software, Kriging approximation method and genetic algorithms is developed for structural optimization. With the developed program, optimum design processes of several structural design problems are investigated. The results show that the proposed method is reliable and in giving fast and satisfactory convergent solutions.
Subjects
Genetic algorithms, Structural optimization, Kriging approximation, Evolution control
Type
thesis
File(s)![Thumbnail Image]()
Loading...
Name
ntu-97-R95522604-1.pdf
Size
23.53 KB
Format
Adobe PDF
Checksum
(MD5):62d603a642eba0581b06abd159fd666d