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International Symposium on Spatial and Temporal Databases

SSTD 2017: Advances in Spatial and Temporal Databases pp 24–42Cite as

Hybrid Best-First Greedy Search for Orienteering with Category Constraints

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10411))

Abstract

We develop an approach for solving rooted orienteering problems with category constraints as found in tourist trip planning and logistics. It is based on expanding partial solutions in a systematic way, prioritizing promising ones, which reduces the search space we have to traverse during the search. The category constraints help in reducing the space we have to explore even further. We implement an algorithm that computes the optimal solution and also illustrate how our approach can be turned into an anytime approximation algorithm, yielding much faster run times and guaranteeing lower bounds on the quality of the solution found. We demonstrate the effectiveness of our algorithms by comparing them to the state-of-the-art approach and an optimal algorithm based on dynamic programming, showing that our technique clearly outperforms these methods.

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Notes

  1. 1.

    The icons are from icons8.com, used under Creative Commons License CC BY-ND 3.0. To view a copy, visit https://creativecommons.org/licenses/by-nd/3.0/.

  2. 2.

    Due to the cut ratio, we did not run this experiment for the real-world data sets, as it would have taken too much time.

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Author information

Authors and Affiliations

  1. Free University of Bozen-Bolzano, Bolzano, Italy

    Paolo Bolzoni & Sven Helmer

Authors
  1. Paolo Bolzoni
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  2. Sven Helmer
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Corresponding author

Correspondence to Sven Helmer .

Editor information

Editors and Affiliations

  1. Institute of Computer Science, Heidelberg University, Heidelberg, Germany

    Michael Gertz

  2. George Mason University, Fairfax, Virginia, USA

    Matthias Renz

  3. University of Queensland, Brisbane, Queensland, Australia

    Xiaofang Zhou

  4. ESRI, University of Minnesota, Minneapolis, Minnesota, USA

    Erik Hoel

  5. Auburn University, Auburn, Alabama, USA

    Wei-Shinn Ku

  6. Free University of Berlin, Dahlem, Berlin, Germany

    Agnes Voisard

  7. Microsoft, Redmond, Washington, USA

    Chengyang Zhang

  8. California State University, Sacramento, California, USA

    Haiquan Chen

  9. LinkedIn, Sunnyvale, California, USA

    Liang Tang

  10. University of North Texas, Denton, Texas, USA

    Yan Huang

  11. Virginia Tech, Falls Church, Virginia, USA

    Chang-Tien Lu

  12. Oracle, Redwood Shores, California, USA

    Siva Ravada

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Bolzoni, P., Helmer, S. (2017). Hybrid Best-First Greedy Search for Orienteering with Category Constraints. In: Gertz, M., et al. Advances in Spatial and Temporal Databases. SSTD 2017. Lecture Notes in Computer Science(), vol 10411. Springer, Cham. https://doi.org/10.1007/978-3-319-64367-0_2

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  • DOI: https://doi.org/10.1007/978-3-319-64367-0_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-64366-3

  • Online ISBN: 978-3-319-64367-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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