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Data Science in Maritime and City Logistics: Data-driven Solutions for Logistics and Sustainability

Editor

Listed:
  • Jahn, Carlos
  • Kersten, Wolfgang
  • Ringle, Christian M.

Abstract

This volume contains research contributions by an international group of authors addressing innovative and technology-based approaches for logistics and sustainability. They present simulation studies, systems and models for optimizations and digitalized solutions with a focus on maritime as well port and city logistics. This volume, edited by Carlos Jahn, Wolfgang Kersten, and Christian Ringle, provides valuable insights into digital transformation in logistics with regard to: - Maritime Logistics - Port Logistics - City Logistics - Sustainability - Business Analytics

Individual chapters are listed in the "Chapters" tab

Suggested Citation

  • Jahn, Carlos & Kersten, Wolfgang & Ringle, Christian M. (ed.), 2020. "Data Science in Maritime and City Logistics: Data-driven Solutions for Logistics and Sustainability," Proceedings of the Hamburg International Conference of Logistics (HICL), Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management, volume 30, number 30.
    • Handle: RePEc:zbw:hiclpr:30
    DOI: 10.15480/882.3101
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    References listed on IDEAS

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    1. Chandra Ade Irawan & Graham Wall & Dylan Jones, 2019. "An optimisation model for scheduling the decommissioning of an offshore wind farm," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 41(2), pages 513-548, June.
    2. Breton, Simon-Philippe & Moe, Geir, 2009. "Status, plans and technologies for offshore wind turbines in Europe and North America," Renewable Energy, Elsevier, vol. 34(3), pages 646-654.
    3. Kerkhove, L.-P. & Vanhoucke, M., 2017. "Optimised scheduling for weather sensitive offshore construction projects," Omega, Elsevier, vol. 66(PA), pages 58-78.
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