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Hub Labels: Theory and Practice

  • Conference paper
Experimental Algorithms (SEA 2014)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8504))

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Abstract

The Hub Labeling algorithm (HL) is an exact shortest path algorithm with excellent query performance on some classes of problems. It precomputes some auxiliary information (stored as a label) for each vertex, and its query performance depends only on the label size. While there are polynomial-time approximation algorithms to find labels of approximately optimal size, practical solutions use hierarchical hub labels (HHL), which are faster to compute but offer no guarantee on the label size. We improve the theoretical and practical performance of the HL approximation algorithms, enabling us to compute such labels for moderately large problems. Our comparison shows that HHL algorithms scale much better and find labels that usually are not much bigger than the theoretically justified HL labels.

Part of this work done while the author was at Microsoft Research.

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Author information

Authors and Affiliations

  1. Microsoft Research, 1065 La Avenida, Mountain View, CA, 94043, USA

    Daniel Delling, Andrew V. Goldberg & Renato F. Werneck

  2. Department of Mech. and Math., Moscow State University, 1 Leninskiye Gory, Moscow, 119991, Russia

    Ruslan Savchenko

Authors
  1. Daniel Delling
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  2. Andrew V. Goldberg
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  3. Ruslan Savchenko
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  4. Renato F. Werneck
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Editor information

Editors and Affiliations

  1. School of IT, University of Sydney, Building J12, 2006, Sydney, NSW, Australia

    Joachim Gudmundsson

  2. Department of Computer Science, University of Copenhagen, Universitetsparken 5, 2100, Copenhagen East, Denmark

    Jyrki Katajainen

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© 2014 Springer International Publishing Switzerland

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Delling, D., Goldberg, A.V., Savchenko, R., Werneck, R.F. (2014). Hub Labels: Theory and Practice. In: Gudmundsson, J., Katajainen, J. (eds) Experimental Algorithms. SEA 2014. Lecture Notes in Computer Science, vol 8504. Springer, Cham. https://doi.org/10.1007/978-3-319-07959-2_22

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  • DOI: https://doi.org/10.1007/978-3-319-07959-2_22

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-07958-5

  • Online ISBN: 978-3-319-07959-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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