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The Capacitated Vehicle Routing Problem with Evidential Demands: A Belief-Constrained Programming Approach

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Belief Functions: Theory and Applications (BELIEF 2016)

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Abstract

This paper studies a vehicle routing problem, where vehicles have a limited capacity and customer demands are uncertain and represented by belief functions. More specifically, this problem is formalized using a belief function based extension of the chance-constrained programming approach, which is a classical modeling of stochastic mathematical programs. In addition, it is shown how the optimal solution cost is influenced by some important parameters involved in the model. Finally, some instances of this difficult problem are solved using a simulated annealing metaheuristic, demonstrating the feasibility of the approach.

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Author information

Authors and Affiliations

  1. University of Artois, EA 3926, Laboratoire de Génie Informatique et d’Automatique de l’Artois (LGI2A), 62400, Béthune, France

    Nathalie Helal, Frédéric Pichon, David Mercier & Éric Lefèvre

  2. Conservatoire National des Arts et Métiers, EA 4629, Cedric, 75003, Paris, France

    Daniel Porumbel

Authors
  1. Nathalie Helal
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  2. Frédéric Pichon
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  3. Daniel Porumbel
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  4. David Mercier
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  5. Éric Lefèvre
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Corresponding author

Correspondence to Nathalie Helal .

Editor information

Editors and Affiliations

  1. Czech Academy of Sciences, nstitute of Information Theory and Automation, Prague , Czech Republic

    Jiřina Vejnarová

  2. Czech Academy of Sciences, Institute of Information Theory and Automation, Prague, Czech Republic

    Václav Kratochvíl

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© 2016 Springer International Publishing Switzerland

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Helal, N., Pichon, F., Porumbel, D., Mercier, D., Lefèvre, É. (2016). The Capacitated Vehicle Routing Problem with Evidential Demands: A Belief-Constrained Programming Approach. In: Vejnarová, J., Kratochvíl, V. (eds) Belief Functions: Theory and Applications. BELIEF 2016. Lecture Notes in Computer Science(), vol 9861. Springer, Cham. https://doi.org/10.1007/978-3-319-45559-4_22

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  • DOI: https://doi.org/10.1007/978-3-319-45559-4_22

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-45558-7

  • Online ISBN: 978-3-319-45559-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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