Metaheuristics for Dynamic Vehicle Routing

  • Mostepha R. Khouadjia
  • Briseida Sarasola
  • Enrique Alba
  • El-Ghazali Talbi
  • Laetitia Jourdan
Part of the Studies in Computational Intelligence book series (SCI, volume 433)


Combinatorial optimization problems are usually modeled in a static fashion. In this kind of problems, all data are known in advance, i.e. before the optimization process has started. However, in practice, many problems are dynamic, and change while the optimization is in progress. For example, in the Dynamic Vehicle Routing Problem (DVRP), which is one of the most challenging combinatorial optimization tasks, the aim consists in designing the optimal set of routes for a fleet of vehicles in order to serve a given set of customers. However, new customer orders arrive while the working day plan is in progress. In this case, routes must be reconfigured dynamically while executing the current simulation. The DVRP is an extension of the conventional routing problem, its main interest being the connection to many real-word applications (repair services, courier mail services, dial-a-ride services, etc.). In this chapter, the DVRP is examined, and a survey on solving methods such as population-based metaheuristics and trajectory-based metaheuristics is exposed. Dynamic performances measures of different metaheuristics are assessed using dedicated indicators for the dynamic environment.


Particle Swarm Optimization Tabu Search Dynamic Vehicle Vehicle Route Problem Transportation Research Part 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Mostepha R. Khouadjia
    • 2
  • Briseida Sarasola
    • 1
  • Enrique Alba
    • 1
  • El-Ghazali Talbi
    • 2
  • Laetitia Jourdan
    • 2
  1. 1.Departamento de Lenguajes y Ciencias de la ComputaciónUniversidad de Málaga, E.T.S.I. InformáticaMálagaSpain
  2. 2.INRIA Lille Nord-Europe, Parc Scientifique de la Haute-BorneVilleneuve d’Ascq CedexFrance

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