Sawant, Rushikesh
(2015)
Improving Results of Differential
Evolution Algorithm.
Masters thesis, National University of Ireland Maynooth.
Abstract
Optimisation problems are of prime importance in scientific and engineering
communities. Many day-to-day tasks in these fields can be classified as
optimisation problems. Due to their enormous solution spaces, optimisation
problems frequently lie in class NP. In such cases, engineers and researchers
have to rely on algorithms and techniques that can find sub-optimal solutions
to these problems. One of the most dependable algorithms for numerical optimisation
problems is Differential Evolution (DE). Since its introduction in the
mid 1990’s, DE has been on the fore front when it comes to applicability of optimisation
algorithms to variety of real-parameter optimisation problems. This
popularity of DE has driven intensive research to further improve its capability
to find optimal solutions.
In this thesis we present a variant of DE to produce improved solutions
with greater reliability. In doing so, we introduce a novel strategy to incorporate
ancestral vectors into the optimisation process. We show that a controlled
introduction of ancestral vectors into the optimisation process has a generally
positive influence on convergence rate of the algorithm. Evaluation of the proposed
algorithm forms a major part of this work, as an empirical evidence
serves to demonstrate the performance of stochastic algorithms. The resulting
implementation of the algorithm is made available as an open source software
along with its reference manual.
Item Type: |
Thesis
(Masters)
|
Additional Information: |
Taught Masters Thesis for the Erasmus Mundus MSc in Dependable Software Systems |
Keywords: |
Improving Results; Differential Evolution Algorithm; |
Academic Unit: |
Faculty of Science and Engineering > Computer Science |
Item ID: |
7091 |
Depositing User: |
IR eTheses
|
Date Deposited: |
04 May 2016 11:07 |
URI: |
|
Use Licence: |
This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available
here |
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