Design Optimization based on Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@PhdThesis{Alvarez:thesis,
  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",
  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",
}

Genetic Programming entries for Luis F Alvarez

Citations