In modern day engineering, the designer has become more and more dependent on
computer simulation. Oftentimes, computational cost and convergence accuracy
accompany these simulations to reach global solutions for engineering design problems
causes traditional optimization techniques to perform poorly. To overcome these issues
nontraditional optimization algorithms based region elimination and space exploration
are introduced. Approximation models, which are also known as metamodels or surrogate
models, are used to explore and give more information about the design space that needs
to be explored. Usually the approximation models are constructed in the promising
regions where global solutions are expected to exist. The approximation models imitate
the original expensive function, black-box function, and contribute towards getting
comparably acceptable solutions with fewer resources and at low computation cost.
The primary contributions of this dissertation are associated with the development of
new methods for exploring the design space for large scale computer simulations.
Primarily, the proposed design space exploration procedure uses a hierarchical
partitioning method to help mitigate the curse of dimensionality often associated with the
analysis of large scale systems.
The research presented in this dissertation focuses on introducing new optimization
algorithms based on metamodeling techniques that alleviate the burden of the
computation cost associated with complex engineering design problems. Three new
global optimization algorithms were introduced in this dissertation, Approximated
Unimodal Region Elimination (AUMRE), Space Exploration and Unimodal Region
Elimination (SEUMRE), and Mixed Surrogate Space Exploration (MSSE) for
computation intensive and black-box engineering design optimization problems. In these
algorithms, the design space was divided into many subspaces and the search was
focused on the most promising regions to reach global solutions with the resources
available and with less computation cost.
Metamodeling techniques such as Response Surface Method (RSM), Radial Basis
Function (RBF), and Kriging (KRG) are introduced and used in this work. RSM has been
used because of its advantages such as being easy to construct, understand and
implement. Also due to its smoothing capability, it allows quick convergence of noisy
functions in the optimization. RBF has the advantage of smoothing data and interpolating
them. KRG metamodels can provide accurate predictions of highly nonlinear or irregular
behaviours. These features in metamodeling techniques have contributed largely towards
obtaining comparably accurate global solutions besides reducing the computation cost
and resources.
Many multi-objective optimization algorithms, specifically those used for engineering
problems and applications involve expensive fitness evaluations. In this dissertation, a
new multi-objective global optimization algorithm for black-box functions is also
introduced and tested on benchmark test problems and real life engineering applications.
Finally, the new proposed global optimization algorithms were tested using benchmark
global optimization test problems to reveal their pros and cons. A comparison with other
well known and recently introduced global optimization algorithms were carried out to
highlight the proposed methods’ advantages and strength points. In addition, a number of
practical examples of global optimization in industrial designs were used and optimized
to further test these new algorithms. These practical examples include the design
optimization of automotive Magnetorheological Brake Design and the design
optimization of two-mode hybrid powertrains for new hybrid vehicles. It is shown that
the proposed optimization algorithms based on metamodeling techniques comparably
provide global solutions with the added benefits of fewer function calls and the ability to
efficiently visualize the design space. / Graduate
| Identifer | oai:union.ndltd.org:uvic.ca/oai:dspace.library.uvic.ca:1828/3325 |
| Date | 30 May 2011 |
| Creators | Younis, Adel Ayad Hassouna |
| Contributors | Dong, Zuomin |
| Source Sets | University of Victoria |
| Language | English, English |
| Detected Language | English |
| Type | Thesis |
| Rights | Available to the World Wide Web |
Page generated in 0.0016 seconds