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

  • Nathalie Helal
  • Frédéric Pichon
  • Daniel Porumbel
  • David Mercier
  • Éric Lefèvre
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9861)

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.

Keywords

Vehicle routing problem Stochastic programming Chance-constrained programming Belief functions 

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Nathalie Helal
    • 1
  • Frédéric Pichon
    • 1
  • Daniel Porumbel
    • 2
  • David Mercier
    • 1
  • Éric Lefèvre
    • 1
  1. 1.University of Artois, EA 3926, Laboratoire de Génie Informatique et d’Automatique de l’Artois (LGI2A)BéthuneFrance
  2. 2.Conservatoire National des Arts et Métiers, EA 4629, CedricParisFrance

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