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Genetic and Evolutionary Computation Conference

GECCO 2003: Genetic and Evolutionary Computation — GECCO 2003 pp 646–656Cite as

A Hybrid Genetic Algorithm for the Capacitated Vehicle Routing Problem

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2723))

Abstract

Recently proved successful for variants of the vehicle routing problem (VRP) involving time windows, genetic algorithms have not yet shown to compete or challenge current best search techniques in solving the classical capacitated VRP. In this paper, a hybrid genetic algorithm to address the capacitated vehicle routing problem is proposed. The basic scheme consists in concurrently evolving two populations of solutions to minimize total traveled distance using genetic operators combining variations of key concepts inspired from routing techniques and search strategies used for a time-variant of the problem to further provide search guidance while balancing intensification and diversification. Results from a computational experiment over common benchmark problems report the proposed approach to be very competitive with the best-known methods.

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Author information

Authors and Affiliations

  1. Decision Support Technology Section, Defence Research and Development Canada - Valcartier, 2459 Pie-XI Blvd. North, Val-Bélair, PQ, Canada, G3J 1X5

    Jean Berger & Mohamed Barkaoui

Authors
  1. Jean Berger
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  2. Mohamed Barkaoui
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Editor information

Editors and Affiliations

  1. Lawrence Livermore National Laboratory, Center for Applied Scientific Computing (CASC), 7000 East Avenue, L-561, Livermore, CA, 94550, USA

    Erick Cantú-Paz

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© 2003 Springer-Verlag Berlin Heidelberg

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Berger, J., Barkaoui, M. (2003). A Hybrid Genetic Algorithm for the Capacitated Vehicle Routing Problem. In: Cantú-Paz, E., et al. Genetic and Evolutionary Computation — GECCO 2003. GECCO 2003. Lecture Notes in Computer Science, vol 2723. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45105-6_80

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  • DOI: https://doi.org/10.1007/3-540-45105-6_80

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-40602-0

  • Online ISBN: 978-3-540-45105-1

  • eBook Packages: Springer Book Archive

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