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International Conference on Computer Aided Systems Theory

EUROCAST 2015: Computer Aided Systems Theory – EUROCAST 2015 pp 393–400Cite as

Diversity-Based Offspring Selection Criteria for Genetic Algorithms

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9520))

Abstract

Genetic algorithms can be affected by an early loss of diversity in their populations called premature convergence. To address this problem, this paper presents two extensions for the offspring selection genetic algorithm. Both extensions are based on diversity maintenance mechanisms applied when selecting offspring for the next generation. The first approach focuses on producing solutions that feature a predefined quality improvement as well as an appropriate structural distance from their parents. The second approach monitors the average diversity of the population and selects more diverse offspring if the population does not meet a predefined diversity. We show that these algorithms allow to control diversity and are useful methods for influencing the development of the population independent of the algorithms other parameters.

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Notes

  1. 1.

    http://www.iwr.uni-heidelberg.de/groups/comopt/software/TSPLIB95/.

  2. 2.

    http://dev.heuristiclab.com.

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Authors and Affiliations

  1. Heuristic and Evolutionary Algorithms Laboratory, School of Informatics, Communications and Media University of Applied Sciences Upper Austria, Campus Hagenberg, Softwarepark 11, 4232, Hagenberg, Austria

    Andreas Scheibenpflug, Stefan Wagner & Michael Affenzeller

  2. Institute for Formal Models and Verification, Johannes Kepler University Linz, Altenberger Straße 69, 4040, Linz, Austria

    Andreas Scheibenpflug & Michael Affenzeller

Authors
  1. Andreas Scheibenpflug
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  2. Stefan Wagner
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  3. Michael Affenzeller
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Corresponding author

Correspondence to Andreas Scheibenpflug .

Editor information

Editors and Affiliations

  1. de Gran Canaria, Universidad de las Palmas de Gran Canari, Las Palmas de Gran Canaria, Spain

    Roberto Moreno-Díaz

  2. Johannes Kepler University Linz, Linz, Austria

    Franz Pichler

  3. de Gran Canaria, Universidad de las Palmas de Gran Canari, Las Palmas de Gran Canaria, Spain

    Alexis Quesada-Arencibia

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Scheibenpflug, A., Wagner, S., Affenzeller, M. (2015). Diversity-Based Offspring Selection Criteria for Genetic Algorithms. In: Moreno-Díaz, R., Pichler, F., Quesada-Arencibia, A. (eds) Computer Aided Systems Theory – EUROCAST 2015. EUROCAST 2015. Lecture Notes in Computer Science(), vol 9520. Springer, Cham. https://doi.org/10.1007/978-3-319-27340-2_49

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  • DOI: https://doi.org/10.1007/978-3-319-27340-2_49

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-27339-6

  • Online ISBN: 978-3-319-27340-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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