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European Symposium on Algorithms

ESA 2012: Algorithms – ESA 2012 pp 169–180Cite as

Time-Dependent Route Planning with Generalized Objective Functions

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Part of the Lecture Notes in Computer Science book series (LNTCS,volume 7501)

Abstract

We consider the problem of finding routes in road networks that optimize a combination of travel time and additional time-invariant costs. These could be an approximation of energy consumption, distance, tolls, or other penalties. The resulting problem is NP-hard, but if the additional cost is proportional to driving distance we can solve it optimally on the German road network within 2.3 s using a multi-label A* search. A generalization of time-dependent contraction hierarchies to the problem yields approximations with negligible errors using running times below 5 ms which makes the model feasible for high-throughput web services. By introducing tolls we get considerably harder instances, but still we have running times below 41 ms and very small errors.

Keywords

  • Travel Time
  • Road Network
  • Destination Node
  • Optimal Route
  • Bend Point

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.

Partially supported by DFG project SA 933/5-1,2.

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Author information

Authors and Affiliations

  1. Karlsruhe Institute of Technology (KIT), 76128, Karlsruhe, Germany

    Gernot Veit Batz & Peter Sanders

Authors
  1. Gernot Veit Batz
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  2. Peter Sanders
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Editor information

Editors and Affiliations

  1. Department of Mathematics, University of Haifa, Mount Carmel, 31905, Haifa, Israel

    Leah Epstein

  2. Dipartimento di Informatica, Università di Pisa, Largo B. Pontecorvo 3, 56100, Pisa, Italy

    Paolo Ferragina

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Batz, G.V., Sanders, P. (2012). Time-Dependent Route Planning with Generalized Objective Functions. In: Epstein, L., Ferragina, P. (eds) Algorithms – ESA 2012. ESA 2012. Lecture Notes in Computer Science, vol 7501. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33090-2_16

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  • DOI: https://doi.org/10.1007/978-3-642-33090-2_16

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-33089-6

  • Online ISBN: 978-3-642-33090-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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