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Quantitative Analysis of Locally Geometric Semantic Crossover

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Parallel Problem Solving from Nature - PPSN XII (PPSN 2012)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7491))

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Abstract

We investigate the properties of locally geometric semantic crossover (LGX), a genetic programming search operator that is approximately semantically geometric on the level of homologous code fragments. For a pair of corresponding loci in the parents, LGX finds a semantically intermediate procedure from a library prepared prior to evolutionary run, and creates an offspring by using such procedure as replacement code. LGX proves superior when compared to standard subtree crossover and other control methods in terms of search convergence, test-set performance, and time required to find a high-quality solution. This paper focuses in particular the impact of homology and program semantic on LGX performance.

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Authors and Affiliations

  1. Institute of Computing Science, Poznan University of Technology, Poznań, Poland

    Krzysztof Krawiec & Tomasz Pawlak

Authors
  1. Krzysztof Krawiec
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  2. Tomasz Pawlak
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Editor information

Editors and Affiliations

  1. Centro de Investigacion y de Estudios, Avanzados del Instituto Politecnico Nacional (CINVESTAV-IPN), Departmento de Computation, Av. IPN No. 2508, Col. San Pedro Zacatenco, 0360, Mexico, D.F., Mexico

    Carlos A. Coello Coello

  2. Department of Mathematics and Computer Science, University of Catania, V.le A. Doria 6, 95125, Catania, Italy

    Vincenzo Cutello  & Mario Pavone  & 

  3. Kanpur Genetic Algorithms Laboratory (KanGAL), Indian Institute of Technology, Kanpur, Kanpur, India

    Kalyanmoy Deb

  4. Department of Computer Science, University of New, Mexico, USA

    Stephanie Forrest

  5. Department of Mathematics and Computer Science, University of Catania, Viale A. Doria 6, 95125, Catania, Italy

    Giuseppe Nicosia

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© 2012 Springer-Verlag Berlin Heidelberg

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Krawiec, K., Pawlak, T. (2012). Quantitative Analysis of Locally Geometric Semantic Crossover. In: Coello, C.A.C., Cutello, V., Deb, K., Forrest, S., Nicosia, G., Pavone, M. (eds) Parallel Problem Solving from Nature - PPSN XII. PPSN 2012. Lecture Notes in Computer Science, vol 7491. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32937-1_40

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  • DOI: https://doi.org/10.1007/978-3-642-32937-1_40

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-32936-4

  • Online ISBN: 978-3-642-32937-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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