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Vehicle routing with stochastic time-dependent travel times

Listed author(s):
  • PEREMANS, Herbert

Assigning and scheduling vehicle routes in a stochastic time-dependent environment is a crucial management problem. The assumption that in a real-life environment everything goes according to an a priori determined static schedule is unrealistic. Our methodology builds on earlier work in which the traffic congestion is captured based on queueing theory in an analytical way and applied to the VRP problem. In this paper, we introduce the variability in the traffic flows into the model. This allows for an evaluation of the routes based on the uncertainty involved. Different experiments show that the risk taking/avoiding behaviour of the planner can be taken into account during optimization. As more weight is contributed to the variability component, the resulting optimal route will be slightly slower, but more reliable. The solution quality in terms of the 95th-percentile of the travel time distribution (assumed lognormal) will also improve.

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Paper provided by University of Antwerp, Faculty of Applied Economics in its series Working Papers with number 2007018.

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Length: 28 pages
Date of creation: Sep 2007
Handle: RePEc:ant:wpaper:2007018
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  1. Gendreau, Michel & Laporte, Gilbert & Seguin, Rene, 1996. "Stochastic vehicle routing," European Journal of Operational Research, Elsevier, vol. 88(1), pages 3-12, January.
  2. VAN WOENSEL, Tom & CRETEN, Ruth & VANDAELE, Nico J., "undated". "Managing the environmental externalities of traffic logistics: The issue of emissions," Working Papers 2000022, University of Antwerp, Faculty of Applied Economics.
  3. Michel Gendreau & Alain Hertz & Gilbert Laporte, 1994. "A Tabu Search Heuristic for the Vehicle Routing Problem," Management Science, INFORMS, vol. 40(10), pages 1276-1290, October.
  4. Van Woensel, T. & Kerbache, L. & Peremans, H. & Vandaele, N., 2008. "Vehicle routing with dynamic travel times: A queueing approach," European Journal of Operational Research, Elsevier, vol. 186(3), pages 990-1007, May.
  5. Michael J. Best & Robert R. Grauer, 1991. "Sensitivity Analysis for Mean-Variance Portfolio Problems," Management Science, INFORMS, vol. 37(8), pages 980-989, August.
  6. Robert R. Grauer & Nils H. Hakansson, 1993. "On the Use of Mean-Variance and Quadratic Approximations in Implementing Dynamic Investment Strategies: A Comparison of Returns and Investment Policies," Management Science, INFORMS, vol. 39(7), pages 856-871, July.
  7. Laoucine Kerbache & T. Van Woensel & H. Peremans & N. Vandaele, 2007. "A Queuing Framework for Routing Problems with Time-dependent Travel Times," Post-Print halshs-00170625, HAL.
  8. Pirlot, Marc, 1996. "General local search methods," European Journal of Operational Research, Elsevier, vol. 92(3), pages 493-511, August.
  9. WUYTS, Bart & VAN WOENSEL, Tom & VANDAELE, Nico, 2004. "Validating state-dependent queueing models for uninterrupted trafic flows using simulation," Working Papers 2004001, University of Antwerp, Faculty of Applied Economics.
  10. Ichoua, Soumia & Gendreau, Michel & Potvin, Jean-Yves, 2003. "Vehicle dispatching with time-dependent travel times," European Journal of Operational Research, Elsevier, vol. 144(2), pages 379-396, January.
  11. Laporte, Gilbert, 1992. "The vehicle routing problem: An overview of exact and approximate algorithms," European Journal of Operational Research, Elsevier, vol. 59(3), pages 345-358, June.
  12. VANDAELE, Nico & VAN WOENSEL, Tom & VERBRUGGEN, Aviel, 1999. "A queueing based traffic flow model," Working Papers 1999015, University of Antwerp, Faculty of Applied Economics.
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