- author = "Michael Cilliers",
- title = "Maintaining population diversity in evolutionary algorithms via epigenetics and speciation",
- school = "Academy Computer Science and Software Engineering, University of Johannesburg",
- year = "2022",
- address = "South Africa",
- month = nov,
- keywords = "genetic algorithms, genetic programming, Evolutionary computation, Species",
- language = "eng",
-
URL = "
https://hdl.handle.net/10210/504017",
-
URL = "https://www.proquest.com/dissertations-theses/maintaining-population-diversity-evolutionary/docview/3132878141/se-2",
- size = "144 pages",
- abstract = "When working with evolutionary algorithms, a balance between exploration and exploitation has to be maintained. The main driver of exploration is the reproduction operation, which is dependent on population diversity to enable effective exploration. The lack of population diversity can thus become a problem if exploration is required during the later stages of the algorithm. One example where this is relevant is when working with dynamic environments. If a change occurs in the environment, the algorithm might require some exploration to adapt to the change. This research aims to demonstrate that if an algorithm is able to maintain population diversity during the latter of its execution, it will be able to adapt to changes more effectively. This research produced a set of novel algorithms to explore different methods of maintaining population diversity. The first group of developed algorithms draws inspiration from gene methylation by adding non-coding genes to the chromosome. The non-coding genes can then act as a reservoir of genetic diversity after the algorithm converges and the diversity in the expressed genes diminishes. The second algorithm implemented parapatric speciation in an evolutionary algorithm. The algorithm attempts to divide the population into separate species, which then populate different areas of the search space. Testing of the developed algorithm showed that it is possible to maintain more diversity in the latter generations of the algorithm. The developed algorithms were also able to adapt more effectively to change in the environment, indicating that the algorithms were able to use the increased diversity when required. Finally, the research showed that the maintaining of diversity is not the only option for allowing exploration in the latter stages of an algorithm. Algorithms that are less effective at maintaining diversity, but are able to rapidly produce diversity when required are also able to shift focus to exploration when adapting to change in the environment.",
-
notes = "Also known as \cite{CilliersMichael2022Mpdi}
Cilliers_Michael_Wtm.pdf
Identifiers 9927009507691
Order No. 31715765 Available from ProQuest Dissertations Theses Global. (3132878141)
Promotor: DA Coulter",
