Exploiting Knowledge About Future Demands for Real-Time Vehicle Dispatching

Soumia Ichoua (), Michel Gendreau () and Jean-Yves Potvin ()
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Soumia Ichoua: Département d’opérations et systèmes de décision, and Centre de recherche sur les technologies de l’organisation réseau, Université Laval, Québec, Québec, Canada G1K 7P4
Michel Gendreau: Département d’informatique et de recherche opérationnelle, and Centre de recherche sur les transports, Université de Montréal, C.P. 6128, succursale Centre-ville, Montréal, Québec, Canada H3C 3J7
Jean-Yves Potvin: Département d’informatique et de recherche opérationnelle, and Centre de recherche sur les transports, Université de Montréal, C.P. 6128, succursale Centre-ville, Montréal, Québec, Canada H3C 3J7

Transportation Science, 2006, vol. 40, issue 2, 211-225

Abstract: An important, but seldom investigated, issue in the field of dynamic vehicle routing and dispatching is how to exploit information about future events to improve decision making. In this paper, we address this issue in a real-time setting with a strategy based on probabilistic knowledge about future request arrivals to better manage the fleet of vehicles. More precisely, the new strategy introduces dummy customers (representing forecasted requests) in vehicle routes to provide a good coverage of the territory. This strategy is assessed through computational experiments performed in a simulated environment.

Keywords: vehicle dispatching; real time; probabilistic knowledge; future events; parallel tabu search (search for similar items in EconPapers)
Date: 2006
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Citations: View citations in EconPapers (72)

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Persistent link: https://EconPapers.repec.org/RePEc:inm:ortrsc:v:40:y:2006:i:2:p:211-225

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