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An Effective Large Neighborhood Search for the Team Orienteering Problem with Time Windows

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Computational Logistics (ICCL 2017)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10572))

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Abstract

We propose an effective metaheuristic for the Team Orienteering Problem with Time Windows. The metaheuristic is based on the principle of Large Neighborhood Search and can outperform the performance of algorithms available in the literature. We provide computational experiments for well known benchmark instances and are able to compute new best solutions for 17 of these instances. On average, the gap between our results and best known solutions so far is below 1%, and our solution approach yields 70% of the best known solutions available in the literature. The new results can serve as benchmarks for future computational studies.

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Author information

Authors and Affiliations

  1. CD Laboratory for Efficient Intermodal Transport Operations, Department of Business Administration, University of Vienna, Vienna, Austria

    Verena Schmid

  2. Management Science Group, Otto-von-Guericke University Magdeburg, Magdeburg, Germany

    Jan Fabian Ehmke

Authors
  1. Verena Schmid
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  2. Jan Fabian Ehmke
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Corresponding author

Correspondence to Jan Fabian Ehmke .

Editor information

Editors and Affiliations

  1. University of Southampton , Southampton, United Kingdom

    Tolga BektaÅŸ

  2. University of Southampton , Southampton, United Kingdom

    Stefano Coniglio

  3. University of Southampton , Southampton, United Kingdom

    Antonio Martinez-Sykora

  4. University of Hamburg , Hamburg, Germany

    Stefan Voß

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Schmid, V., Ehmke, J.F. (2017). An Effective Large Neighborhood Search for the Team Orienteering Problem with Time Windows. In: Bektaş, T., Coniglio, S., Martinez-Sykora, A., Voß, S. (eds) Computational Logistics. ICCL 2017. Lecture Notes in Computer Science(), vol 10572. Springer, Cham. https://doi.org/10.1007/978-3-319-68496-3_1

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  • DOI: https://doi.org/10.1007/978-3-319-68496-3_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-68495-6

  • Online ISBN: 978-3-319-68496-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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