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STRATEGIES OF AN INTELLIGENT ALGORITHM: An evaluation of genetic algorithm settings for optimizing mobile network coverage
Umeå University, Faculty of Science and Technology, Department of Computing Science.
Umeå University, Faculty of Science and Technology, Department of Computing Science.
2019 (English)Independent thesis Basic level (degree of Bachelor of Fine Arts), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

Th‘is report set out to evaluate control parameters used in a genetic algorithm in the use-case of providing an area with semi-realistic mobile coverage. Th‘e parameters evaluated consisted of the selection method, mutation probability, crossover probability and initial population size. Th‘e parameters were evaluated in terms of mean time to achieve a pre-set coverage threshold.Th‘e genetic algorithm will be used to generate a model of telecom infrastructure that can be used in simulation purposes, where the usage of the real-world infrastructure is considered illegal.‘ The study found a set of control parameters that completed the given task many times faster than the initial parameters. ‘The €final set of parameters consisted of Binary Tournament selection method, 30% mutation probability, 90% crossover probability, and a population size equal to the problem dimension. In conclusion, the study propose additional work to be done to possibly €find even more efficient set of parameters, as the scope of this study virtually eliminates the chance of€ finding a global maximum.

Place, publisher, year, edition, pages
2019. , p. 44
Series
UMNAD ; 1180
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:umu:diva-163177OAI: oai:DiVA.org:umu-163177DiVA, id: diva2:1349818
External cooperation
Tieto
Educational program
Bachelor of Science Programme in Computing Science
Supervisors
Examiners
Available from: 2019-09-10 Created: 2019-09-10 Last updated: 2019-09-10Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
  • ieee
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Language
  • de-DE
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