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A Genetic Algorithm for the Uncapacitated Network Design Problem

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Soft Computing and Industry

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Abstract

In this paper a genetic algorithm (GA) for solving the uncapacitated network design problem (UNDP) is presented. The problem with single source and destinations for each commodity is considered. UNDP is a base in class of the network design problems, but it is still NP-hard. The implementation of GA is additionally improved by caching technique of GA. The computational results on instances up to 50 commodities, 100 nodes and 700 edges are reported.

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Author information

Authors and Affiliations

  1. Institute of Mathematics, Serbian Academy of Sciences and Arts, Strumicka 92/5, 11 000, Belgrade, Serbia, Yugoslavia

    Jozef Kratica

  2. Faculty of Mathematics, University of Belgrade, Studentski trg 16, Belgrade, Serbia, Yugoslavia

    Dušan Tošić & Vladimir Filipović

  3. Institute for Computer Graphics, Vienna Univesity of Technology, Favoritensstasse 9, Vienna, Austria

    Ivana Ljubić

Authors
  1. Jozef Kratica
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  2. Dušan Tošić
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  3. Vladimir Filipović
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  4. Ivana Ljubić
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Editor information

Editors and Affiliations

  1. Enterprise Integration, Cranfield University, Cranfield, Bedford, MK43 0AL, UK

    Rajkumar Roy PhD

  2. Department of Pattern Recognition, Fraunhofer IPK-Berlin, Pascalstrasse 8-9, Berlin, 10587, Germany

    Mario Köppen Diplom-Phys

  3. Institute of Intelligent Electronics, Helsinki University of Technology, Otakaari 5 A, FIN-02150, Espoo, Finland

    Seppo Ovaska PhD

  4. Department of Information Engineering, Mie University, 1515 Kamihama-cho, Tsu, 514-8507, Japan

    Takeshi Furuhashi PhD

  5. Royal Institute of Technology, NADA/CV AP, 10044, Stockholm, Sweden

    Frank Hoffmann

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© 2002 Springer-Verlag London

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Kratica, J., Tošić, D., Filipović, V., Ljubić, I. (2002). A Genetic Algorithm for the Uncapacitated Network Design Problem. In: Roy, R., Köppen, M., Ovaska, S., Furuhashi, T., Hoffmann, F. (eds) Soft Computing and Industry. Springer, London. https://doi.org/10.1007/978-1-4471-0123-9_28

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  • DOI: https://doi.org/10.1007/978-1-4471-0123-9_28

  • Publisher Name: Springer, London

  • Print ISBN: 978-1-4471-1101-6

  • Online ISBN: 978-1-4471-0123-9

  • eBook Packages: Springer Book Archive

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