- author = "L. F. Alvarez",
- title = "Design Optimization based on Genetic Programming",
- school = "Department of Civil and Environmental Engineering, University of Bradford",
- year = "2000",
- address = "UK",
- keywords = "genetic algorithms, genetic programming, Design Optimization, Response Surface Methodology",
-
URL = "
http://www.brad.ac.uk/staff/vtoropov/burgeon/thesis_luis/abstract.pdf",
-
URL = "http://www.brad.ac.uk/staff/vtoropov/burgeon/thesis_luis/contents.pdf",
-
URL = "http://www.brad.ac.uk/staff/vtoropov/burgeon/thesis_luis/chapter1.pdf",
-
URL = "http://www.brad.ac.uk/staff/vtoropov/burgeon/thesis_luis/chapter2.pdf",
-
URL = "http://www.brad.ac.uk/staff/vtoropov/burgeon/thesis_luis/chapter3.pdf",
-
URL = "http://www.brad.ac.uk/staff/vtoropov/burgeon/thesis_luis/chapter4.pdf",
-
URL = "http://www.brad.ac.uk/staff/vtoropov/burgeon/thesis_luis/chapter5.pdf",
-
URL = "http://www.brad.ac.uk/staff/vtoropov/burgeon/thesis_luis/chapter7.pdf",
-
URL = "http://www.brad.ac.uk/staff/vtoropov/burgeon/thesis_luis/references.pdf",
-
URL = "http://www.brad.ac.uk/staff/vtoropov/burgeon/thesis_luis/appendixA.pdf",
-
URL = "http://www.brad.ac.uk/staff/vtoropov/burgeon/thesis_luis/appendixB.pdf",
- size = "v + 132 pages",
-
abstract = "This thesis addresses two problems arising in many
real-life design optimization applications: the high
computational cost of function evaluations and the
presence of numerical noise in the function values. The
response surface methodology is used to construct
approximations of the original model. A major
difficulty in building highly accurate response
surfaces is the selection of the structure of an
approximation function.
A methodology has been developed for the approximation model building using genetic programming. It is implemented in a computer code introducing two new features: the use of design sensitivity information when available, and the allocation and evaluation of tuning parameters in separation from the evolutionary process. A combination of a genetic algorithm and a gradient-based algorithm is used for tuning of the approximation functions. The problem of the choice of a design of experiments in the response surface methodology has been reviewed and a space-filling plan adopted.
The developed methodology and software have been applied to design optimization problems with numerically simulated and experimental responses, demonstrating their considerable potential. The applications cover the approximation of a response function obtained by a finite element model for the detection of damage in steel frames, the creation of an empirical model for the prediction of the shear strength in concrete deep beams and a multicriteria optimization of the process of calcination of Roman cement.",
-
notes = "Approximation model building for design optimization
using the response surface methodology and genetic
programming.
Luis Francisco Alvarez Barrioluengo
Supervisor V.V. Toropov",
