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Elements of Evolutionary Algorithms

  • Rudolf Kruse
  • Christian Borgelt
  • Frank Klawonn
  • Christian Moewes
  • Matthias Steinbrecher
  • Pascal Held
Part of the Texts in Computer Science book series (TCS)

Abstract

Evolutionary algorithms are not fixed procedures, but contain several elements that must be adapted to the optimization problem to be solved. In particular, the encoding of the candidate solution needs to be chosen with care. Although there is no generally valid rule or recipe, we discuss some important properties a good encoding should have. We also turn to the fitness function and review the most common selection techniques as well as how certain undesired effects can be avoided by adapting the fitness function or the selection method. The last section of this chapter is devoted to genetic operators, which serve as tools to explore the search space, and covers sexual and asexual recombination and other variation techniques.

Keywords

Search Space Evolutionary Algorithm Travel Salesman Problem Genetic Operator Good Individual 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. Y. Davidor. Lamarckian Sub-Goal Reward in Genetic Algorithm. Proc. Euro. Conf. on Artificial Intelligence (ECAI, Stockholm, Sweden), 189–194. Pitman, London/Boston, United Kingdom/USA, 1990 Google Scholar
  2. Z. Michalewicz. Genetic Algorithms + Data Structures = Evolution Programs, 3rd (extended) edition. Springer-Verlag, New York, NY, USA, 1996 Google Scholar

Copyright information

© Springer-Verlag London 2013

Authors and Affiliations

  • Rudolf Kruse
    • 1
  • Christian Borgelt
    • 2
  • Frank Klawonn
    • 3
  • Christian Moewes
    • 1
  • Matthias Steinbrecher
    • 4
  • Pascal Held
    • 1
  1. 1.Faculty of Computer ScienceOtto-von-Guericke University MagdeburgMagdeburgGermany
  2. 2.Intelligent Data Analysis & Graphical Models Research UnitEuropean Centre for Soft ComputingMieresSpain
  3. 3.FB InformatikOstfalia University of Applied SciencesWolfenbüttelGermany
  4. 4.SAP Innovation CenterPotsdamGermany

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