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Development of a Framework for Genetic Algorithms
Jönköping University, School of Engineering, JTH, Computer and Electrical Engineering.
2009 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesisAlternative title
Utveckling av ett ramverk för genetiska algoritmer (Swedish)
Abstract [en]

Genetic algorithms is a method of optimization that can be used tosolve many different kinds of problems. This thesis focuses ondeveloping a framework for genetic algorithms that is capable ofsolving at least the two problems explored in the work. Otherproblems are supported by allowing user-made extensions.The purpose of this thesis is to explore the possibilities of geneticalgorithms for optimization problems and artificial intelligenceapplications.To test the framework two applications are developed that look attwo distinct problems, both of which aim at demonstrating differentparts. The first problem is the so called Travelling SalesmanProblem. The second problem is a kind of artificial life simulator,where two groups of creatures, designated predator and prey, aretrying to survive.The application for the Travelling Salesman Problem measures theperformance of the framework by solving such problems usingdifferent settings. The creature simulator on the other hand is apractical application of a different aspect of the framework, wherethe results are compared against predefined data. The purpose is tosee whether the framework can be used to create useful data forthe creatures.The work showed how important a detailed design is. When thework began on the demonstration applications, things were noticedthat needed changing inside the framework. This led to redesigningparts of the framework to support the missing details. A conclusionfrom this is that being more thorough in the planning, andconsidering the possible use cases could have helped avoid thissituation.The results from the simulations showed that the framework iscapable of solving the specified problems, but the performance isnot the best. The framework can be used to solve arbitrary problemsby user-created extensions quite easily.

Place, publisher, year, edition, pages
2009. , 64 p.
Keyword [en]
Genetic algorithms, optimization, c++, Travelling Salesman Problem, artificial intelligence, framework, library
Keyword [sv]
Genetiska algoritmer, optimering, c++, Handelsresandeproblemet, artificiell intelligens, ramverk, bibliotek
National Category
Computer Science
Identifiers
URN: urn:nbn:se:hj:diva-11537OAI: oai:DiVA.org:hj-11537DiVA: diva2:290914
Presentation
(English)
Uppsok
Technology
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Available from: 2010-02-09 Created: 2010-01-28 Last updated: 2010-02-09Bibliographically approved

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fulltext(763 kB)293 downloads
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CiteExportLink to record
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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
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  • text
  • asciidoc
  • rtf