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On the Ability of the One-Point Crossover Operator to Search the Space in Genetic Algorithms

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Artificial Intelligence and Soft Computing (ICAISC 2015)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9119))

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Abstract

In this paper we study the search abilities of binary one-point crossover (1ptc) operator in a genetic algorithm (GA). We show, that under certain conditions, GA is capable of using only a 1ptc operator to explore the entire search space, fighting premature convergence. Further, we prove that to restore the entire space from any two binary chromosomes, each of length n, at least 2n − 1 − 1 one-point crossover operations is needed. This number can serve as a measure for comparing the search speed of the different algorithms. Moreover, we propose an algorithm spanning the search space in the minimal number of crossovers.

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Author information

Authors and Affiliations

  1. Wroclaw Public Library, Sztabowa 95, 53-310, Wroclaw, Poland

    Zbigniew Pliszka

  2. Department of Computer Engineering, Faculty of Electronics, Wroclaw University of Technology, Wyb. Wyspianskiego 27, 50-370, Wroclaw, Poland

    Olgierd Unold

Authors
  1. Zbigniew Pliszka
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  2. Olgierd Unold
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Editor information

Editors and Affiliations

  1. Częstochowa University of Technology, Częstochowa, Poland

    Leszek Rutkowski

  2. Częstochowa University of Technology, Częstochowa, Poland

    Marcin Korytkowski

  3. Częstochowa University of Technology, Częstochowa, Poland

    Rafal Scherer

  4. AGH University of Science and Technology, Krakow, Poland

    Ryszard Tadeusiewicz

  5. University of California, Berkeley, California, USA

    Lotfi A. Zadeh

  6. University of Louisville, Louisville, Kentucky, USA

    Jacek M. Zurada

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© 2015 Springer International Publishing Switzerland

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Pliszka, Z., Unold, O. (2015). On the Ability of the One-Point Crossover Operator to Search the Space in Genetic Algorithms. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L., Zurada, J. (eds) Artificial Intelligence and Soft Computing. ICAISC 2015. Lecture Notes in Computer Science(), vol 9119. Springer, Cham. https://doi.org/10.1007/978-3-319-19324-3_33

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  • DOI: https://doi.org/10.1007/978-3-319-19324-3_33

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-19323-6

  • Online ISBN: 978-3-319-19324-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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