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International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems

IEA/AIE 2000: Intelligent Problem Solving. Methodologies and Approaches pp 611–616Cite as

Nuclear Power Plant Preventive Maintenance Planning Using Genetic Algorithms

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1821))

Abstract

To achieve the highest reliability level of a nuclear power plant operation a preventive maintenance program is used that must be effective and efficient. To improve the existing maintenance a pilot project concerning electrical components was started in the NPP Krsko. We developed and implemented a new co-evolutionary method to optimize preventive maintenance activities by finding an optimal time-plan and selecting appropriate maintenance personnel allocation.

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References

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Author information

Authors and Affiliations

  1. Laboratory for System Design, University of Maribor - FERI, Smetanova 17, SI-2000, Maribor, Slovenia

    Vili Podgorelec & Peter Kokol

  2. Nuclear Power Plant KrskoVrbina 12, Krsko, Slovenia

    Andrej Kunej

Authors
  1. Vili Podgorelec
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  2. Peter Kokol
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  3. Andrej Kunej
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Editor information

Editors and Affiliations

  1. The Center for Advanced Computer Studies, University of Lousiana, 2 Rex Street, Lafayette, LA, 70504-4330, USA

    Rasiah Logananthara

  2. Department of Neural Information Processing, University of Ulm, Oberer Eselsberg, 89069, Ulm, Germany

    Günther Palm

  3. Department of Computer Science, Southwest Texas State University, 601 University Drive, San Marcos, TX, 78666-4616, USA

    Moonis Ali

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© 2000 Springer-Verlag Berlin Heidelberg

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Podgorelec, V., Kokol, P., Kunej, A. (2000). Nuclear Power Plant Preventive Maintenance Planning Using Genetic Algorithms. In: Logananthara, R., Palm, G., Ali, M. (eds) Intelligent Problem Solving. Methodologies and Approaches. IEA/AIE 2000. Lecture Notes in Computer Science(), vol 1821. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45049-1_73

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  • DOI: https://doi.org/10.1007/3-540-45049-1_73

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-67689-8

  • Online ISBN: 978-3-540-45049-8

  • eBook Packages: Springer Book Archive

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