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Chapter

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Title

Combining Semantically-Effective and Geometric Crossover Operators for Genetic Programming

Authors

[ 1 ] Instytut Informatyki, Wydział Informatyki, Politechnika Poznańska | [ P ] employee

Year of publication

2014

Chapter type

paper

Publication language

english

Keywords
EN
  • semantics
  • taxonomy
  • neutrality
  • brood selection
  • experiment
Abstract

EN We propose a way to combine two distinct general patterns for designing semantic crossover operators for genetic programming: geometric semantic approach and semantically-effective approach. In the experimental part we show the synergistic effects of combining these two approaches, which we explain by a major fraction of crossover acts performed by geometric semantic crossover operators being semantically ineffective. The results of the combined approach show significant improvement of performance and high resistance to a premature convergence.

Pages (from - to)

454 - 464

DOI

10.1007/978-3-319-10762-2_45

URL

https://link.springer.com/chapter/10.1007/978-3-319-10762-2_45

Book

Parallel Problem Solving from Nature - PPSN XIII : 13th International Conference, Ljubljana, Slovenia, September 13-17, 2014 : proceedings

Presented on

13th International Conference on Parallel Problem Solving from Nature, PPSN 2014, 13-17.09.2014, Ljubljana, Slovenia

Publication indexed in

WoS (15)

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