Parsimony Pressure versus Multi-objective Optimization for Variable Length Representations

  • Markus Wagner
  • Frank Neumann
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7491)


We contribute to the theoretical understanding of variable length evolutionary algorithms. Such algorithms are very flexible but can encounter the bloat problem which means solutions grow during the optimization run without providing additional benefit. We explore two common mechanisms for dealing with this problem from a theoretical point of view and point out the differences of a parsimony and a multi-objective approach in a rigorous way. As an example to point out the differences, we consider different measures of sortedness for the classical sorting problem which has already been studied in the computational complexity analysis of evolutionary algorithms with fixed length representations.


Evolutionary Algorithm Pareto Front Mutation Operator Correct Position Length Representation 
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.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Markus Wagner
    • 1
  • Frank Neumann
    • 1
  1. 1.School of Computer ScienceUniversity of AdelaideAdelaideAustralia

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