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Optimizing Maritime Preparedness Under Uncertainty – Locating Tugboats Along the Norwegian Coast

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Computational Logistics (ICCL 2021)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 13004))

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Abstract

We study the strategic problem of locating tugboats along the Norwegian coast to optimize maritime preparedness. The problem is formulated as a two-stage stochastic program. In the first stage, we locate the tugboats such that nominal coverage requirements are satisfied, whereas we deploy the located tugboats in the second stage in order to assist vessels in distress. The objective is to minimize the sum of the costs of publicly operated tugboats in the emergency towing service and the expected penalty costs due to insufficient preparedness. We solve the problem using Sample Average Approximation in combination with a self-developed heuristic. Our results indicate that we can achieve a sufficient preparedness level with six tugboats.

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Authors and Affiliations

  1. Department of Industrial Economics and Technology Management, Norwegian University of Science and Technology, Trondheim, Norway

    Julie Louise Musæus, Håkon Nøstvik, Henrik Andersson & Peter Schütz

Authors
  1. Julie Louise Musæus
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  2. Håkon Nøstvik
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  3. Henrik Andersson
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  4. Peter Schütz
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Corresponding author

Correspondence to Peter Schütz .

Editor information

Editors and Affiliations

  1. IEBIS, University of Twente, Enschede, Overijssel, The Netherlands

    Martijn Mes

  2. IEBIS, University of Twente, Enschede, Overijssel, The Netherlands

    Eduardo Lalla-Ruiz

  3. IWI-Institute of Information Systems, University of Hamburg, Hamburg, Germany

    Stefan Voß

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Musæus, J.L., Nøstvik, H., Andersson, H., Schütz, P. (2021). Optimizing Maritime Preparedness Under Uncertainty – Locating Tugboats Along the Norwegian Coast. In: Mes, M., Lalla-Ruiz, E., Voß, S. (eds) Computational Logistics. ICCL 2021. Lecture Notes in Computer Science(), vol 13004. Springer, Cham. https://doi.org/10.1007/978-3-030-87672-2_7

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  • DOI: https://doi.org/10.1007/978-3-030-87672-2_7

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-87671-5

  • Online ISBN: 978-3-030-87672-2

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