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A Genetic Algorithm for the Capacitated Arc Routing Problem and Its Extensions

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Applications of Evolutionary Computing (EvoWorkshops 2001)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2037))

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Abstract

The NP-hard Capacitated Arc Routing Problem (CARP) allows to model urban waste collection or road gritting, for instance. Exact algorithms are still limited to small problems and metaheuristics are required for large scale instances. The paper presents the first genetic algorithm (GA) published for the CARP. This hybrid GA tackles realistic extensions like mixed graphs or prohibited turns. It displays excellent results and outperforms the best metaheuristics published when applied to two standard sets of benchmarks: the average deviations to lower bounds are 0.24 % and 0.69 % respectively, a majority of instances are solved to optimality, and eight best known solutions are improved.

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Author information

Authors and Affiliations

  1. Laboratory for Industrial Systems Optimization, University of Technology of Troyes, 12, Rue Marie Curie, 2060, F, 10010, Troyes Cedex, France

    Wahiba Ramdane-Chérif

Authors
  1. Philippe Lacomme
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  2. Christian Prins
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  3. Wahiba Ramdane-Chérif
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Editor information

Editors and Affiliations

  1. Leiden University, Niels Bohrweg1, 2333, CA, Leiden, The Netherlands

    Egbert J. W. Boers

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© 2001 Springer-Verlag Berlin Heidelberg

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Lacomme, P., Prins, C., Ramdane-Chérif, W. (2001). A Genetic Algorithm for the Capacitated Arc Routing Problem and Its Extensions. In: Boers, E.J.W. (eds) Applications of Evolutionary Computing. EvoWorkshops 2001. Lecture Notes in Computer Science, vol 2037. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45365-2_49

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  • DOI: https://doi.org/10.1007/3-540-45365-2_49

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-41920-4

  • Online ISBN: 978-3-540-45365-9

  • eBook Packages: Springer Book Archive

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