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Adriatic Sea Hub Ports Feeder Service Optimization Using Multi-Criteria Decision-Making Methods

Author

Listed:
  • Dario Medić

    (Faculty of Maritime Studies, University of Split, Ruđera Boškovića 37, 21000 Split, Croatia)

  • Srećko Krile

    (Maritime Department, University of Dubrovnik, Branitelja Dubrovnika 29, 20000 Dubrovnik, Croatia)

  • Igor Jelaska

    (Faculty of Kinesiology, University of Split, Teslina 6, 21000 Split, Croatia)

  • Rino Bošnjak

    (Faculty of Maritime Studies, University of Split, Ruđera Boškovića 37, 21000 Split, Croatia)

Abstract

From a scientific viewpoint, as well as from the perspective of navigation practice, it is clear that the Adriatic Sea feeder service is relatively underdeveloped. Hence, the objective of this study is to suggest a model for selecting the hub port and to optimize the network of seaports engaged in the feeder service. Accordingly, an appropriate hub port has been identified through the methods of multi-criteria decision making and expert assessment, and the optimum shipping route has been calculated by applying the travelling salesman algorithm (TSA). In order to analyze whether there is a possibility of obtaining better optimization results, an integration of a sub-hub port system is suggested. Optimization has been achieved by applying a minimum spanning tree algorithm (MST) and a combination of these algorithms. The proposed methodology for selecting the hub port, sub-hub port and optimizing the feeder network can be implemented globally. The practical application of the achieved model would result in cost minimization, owing to shorter shipping routes or a combination of different transportation means (feeders).

Suggested Citation

  • Dario Medić & Srećko Krile & Igor Jelaska & Rino Bošnjak, 2021. "Adriatic Sea Hub Ports Feeder Service Optimization Using Multi-Criteria Decision-Making Methods," Sustainability, MDPI, vol. 13(21), pages 1-12, November.
  • Handle: RePEc:gam:jsusta:v:13:y:2021:i:21:p:12325-:d:674559
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    References listed on IDEAS

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