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Dynamic Vehicle Routing in Over Congested Urban Areas

  • Antonio G. N. NovaesEmail author
  • Enzo M. Frazzon
  • Paulo J. Burin
Conference paper

Abstract

The solution of dynamic vehicle routing problems has evolved rapidly in the past years due to the development of telecommunication and information technologies. Traffic information systems have been installed in large cities of the world with the objective of reducing the negative effects of bottlenecks in street networks. In developing countries, however, the large investments to install such systems often forbid its extensive use. By analyzing a simple urban routing problem, subject to unexpected and frequent traffic jams, we show with the aid of Sequential Analysis concepts that even under limited technological resources it is possible to obtain significant benefits when adopting a dynamic strategy to handle vehicle routing problems.

References

  1. Daganzo C.F. (1996) Logistics systems analysis, Springer, Berlin.Google Scholar
  2. Flatberg, T., Hasle, G., Kloster, O., Nilssen, E., Riise, A. (2007) Dynamic and stochastic vehicle routing in practice. In: Zeimpekis, V., Tarantilis, C.D., Giaglis, G., Minis, I. Dynamic fleet management. Springer, New York.Google Scholar
  3. Fleischmann, B., Gnutzmann, S., Sandvoß, E. (2004), Dynamic vehicle routing based on on-line traffic information. Transportation Science, 38 (4), pp. 420–433.CrossRefGoogle Scholar
  4. Galvão, L.C., Novaes, A.G., Souza de Cursi, J.E., and Souza, J.C. (2006), A Multiplicatively-weighted Voronoi diagram approach to logistics districting, Computers & Operations Research 33, pp. 93–114.zbMATHCrossRefGoogle Scholar
  5. Ghosh, M., Mukhopadhyay, N. and Sen, P.K. (1997), Sequential estimation, Wiley, New York.zbMATHGoogle Scholar
  6. Goel, A. (2008) Fleet telematics, Springer, New York.zbMATHGoogle Scholar
  7. Lai, T.L. (2001), Sequential analysis: some classical problems and new challenges, Statistica Sinica 11, pp. 303–408.zbMATHMathSciNetGoogle Scholar
  8. Langevin A., Mbaraga P., Campbell J.F. (1996), Continuous approximation models in freight distribution: an overview, Transportation Research – B, V 30, pp. 163-188.CrossRefGoogle Scholar
  9. Larsen, A., Madsen, O., Salomon, M. (2007) Classification of dynamic vehicle routing systems. In: Zeimpekis, V., Tarantilis, C.D., Giaglis, G., Minis, I. Dynamic fleet management. Springer, New York.Google Scholar
  10. Novaes A.G., Graciolli O.D. (1999), Designing multi-vehicle tours in a grid-cell format. European Journal of Operational Research, V 119, pp. 613–634.zbMATHCrossRefGoogle Scholar
  11. Novaes, A.G., Souza de Cursi J.E., and Graciolli, O.D. (2000), A continuous approach to the design of physical distribution systems, Computers & Operations Research 27, pp. 877–893.zbMATHCrossRefGoogle Scholar
  12. Novaes A.G., Souza de Cursi J.E., da Silva A.C.L. and Souza, J.C. (2009), Solving continuous location-districting problems with Voronoi diagrams, Computers & Operations Research 36, pp. 40-59.zbMATHCrossRefGoogle Scholar
  13. Wald, A. (1947), Sequential analysis, Wiley, New York.zbMATHGoogle Scholar
  14. Zeimpekis, V., Minis, I., Mamassis, K., Giaglis, G. (2007) Dynamic management of a delayed delivery vehicle in a city logistics environment. In: Zeimpekis, V., Tarantilis, C.D., Giaglis, G., Minis, I. Dynamic fleet management. Springer, New York.Google Scholar

Copyright information

© Springer -Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Antonio G. N. Novaes
    • 1
    Email author
  • Enzo M. Frazzon
    • 1
  • Paulo J. Burin
    • 1
  1. 1.Department of Industrial EngineeringFederal University of Santa CatarinaSanta CatarinaBrazil

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