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Dynamic Vehicle Routing Based on Online Traffic Information

Fleischmann, Bernhard, Gnutzmann, Stefan, Sandvoß, Elke·2004·Transportation Science

Abstract

With the increasing availability of real-time information and communication systems in logistics, the need for appropriate planning algorithms, which make use of this technology, arises. Customers in transport markets increasingly expect quicker and more flexible fulfillment of their orders, especially in the electronic marketplace. This paper considers a dynamic routing system that dispatches a fleet of vehicles according to customer orders arriving at random during the planning period. Each customer order requires a transport from a pickup location to a delivery location in a given time window. The system disposes of online communication with all drivers and customers and, in addition, disposes of online information on travel times from a traffic management center. This paper presents a planning framework for this situation which, to our knowledge, has not yet been addressed in the literature. It then describes three routing procedures for event-based dispatching, which differ in the length of the planning horizon per event. We focus on the use of dynamic travel time information, which requires dynamic shortest path calculations. The procedures are tested and compared using real-life data of an urban traffic management center and a logistics service provider.

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Metadata

Authors
Fleischmann, B., Gnutzmann, S., & Sandvoß, E.
Venue
Transportation Science
Published
2004-11
Volume
38
Issue
4
Pages
420-433
ISSN
  • 0041-1655 (ISSN-L)
  • 1526-5447
OpenAlex
W2092165528
Cited by
224
References
0
FWCI
38.48
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Dynamic Vehicle Routing Based on Online Traffic Information. https://app.cochat.ai/papers/10.1287/trsc.1030.0074
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Fleischmann, B., Gnutzmann, S., & Sandvoß, E. (2004). Dynamic Vehicle Routing Based on Online Traffic Information. Transportation Science. https://doi.org/10.1287/trsc.1030.0074

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

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