Comparison of methods for developing and using dynamic reduced models for design optimization
Abstract (Summary)
This thesis compares different methods used in developing and using dynamic
reduced models for design optimization. Several methods have been used for forming
functional approximation models with which the GA search is performed more efficiently.
The informed operators approach for search speedup is discussed. Another
hypothesis-instantiation approach in using reduced models has been tested and
compared with the informed operator approach. Chapter one first gives some
background knowledge. Chapter two describes three different methods for forming
reduced models to speed up genetic-algorithm-based design optimization. Chapter
three describes two methods for using reduced models to speed up genetic-algorithmbased
design optimization. Chapter four gives the experimental results and discussion.
Finally, chapter five serves as a summary of the whole thesis.
Index words: GADO, Quickprop, RBF, Quadratic least squares,
Genetic engineering, Informed operators, Reduced models
Comparison of Methods for Developing and Using
Dynamic Reduced Models for Design Optimization
by
Xiao Ni
B.S., Xian Jiaotong University, China, 2000
A Thesis Submitted to the Graduate Faculty
of The University of Georgia in Partial Fulfillment
of the
Requirements for the Degree
Master of Science
Athens, Georgia
2002
c? 2002
Xiao Ni
All Rights Reserved
Comparison of Methods for Developing and Using
Dynamic Reduced Models for Design Optimization
by
Xiao Ni
Approved:
Major Professor: Khaled Rasheed
Committee: Ron McClendon
Charles Cross
Electronic Version Approved:
Gordhan L. Patel
Dean of the Graduate School
The University of Georgia
July 2002
Bibliographical Information:
Advisor:
School:The University of Georgia
School Location:USA - Georgia
Source Type:Master's Thesis
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ISBN:
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