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On the Effectiveness of Genetic Operations in Symbolic Regression

  • Bogdan BurlacuEmail author
  • Michael Affenzeller
  • Michael Kommenda
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9520)

Abstract

This paper describes a methodology for analyzing the evolutionary dynamics of genetic programming (GP) using genealogical information, diversity measures and information about the fitness variation from parent to offspring. We introduce a new subtree tracing approach for identifying the origins of genes in the structure of individuals, and we show that only a small fraction of ancestor individuals are responsible for the evolvement of the best solutions in the population.

Keywords

Genetic programming Evolutionary dynamics Algorithm analysis Symbolic regression 

Notes

Acknowledgments

The work described in this paper was done within the COMET Project Heuristic Optimization in Production and Logistics (HOPL), #843532 funded by the Austrian Research Promotion Agency (FFG).

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Bogdan Burlacu
    • 1
    • 2
    Email author
  • Michael Affenzeller
    • 1
    • 2
  • Michael Kommenda
    • 1
    • 2
  1. 1.Heuristic and Evolutionary Algorithms Laboratory School of Informatics, Communications and MediaUniversity of Applied Sciences Upper AustriaHagenbergAustria
  2. 2.Institute for Formal Models and VerificationJohannes Kepler University LinzLinzAustria

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