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Analysis of passenger ships activity in the oil and gas offshore shipping sector in the North Sea

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Maritime and coastal areas are the lifeblood of many countries. They are vital to the prosperity of countries because they provide trade routes, regulate the climate, are a source of organic and inorganic resources and energy, and provide a place for the public to live and relax. Increasingly, however, there are divergences and barriers to the use of marine areas. On the one hand, available and developed technology and knowledge enable increasingly improved use of the sea. On the other hand, the combined effect of these activities leads to conflicts of interest and the deterioration of the marine environment. The purpose of this study is to analyze the feasibility of using automatic identification system (AIS) maritime traffic data, in terms of its suitability, to correctly assess the utilization of the potential of a specific fleet within the offshore shipping industry. In addition, the authors undertake the task of determining to what extent activities relating to the GPS position of the ship, ship type (i.e., cargo or passenger), ship status (i.e., aground, anchored, moored, not under command, restricted maneuverability, underway sailing, or underway using its engine), ship draught, service speed, total engine power, and deadweight constitute areas and methods for optimizing the use of the offshore fleet under all the conditions previously described that limit this optimization. Given the stated goal, this paper uses both a literature review procedure and statistical methods to conduct a comparative analysis.
Rocznik
Strony
68--78
Opis fizyczny
Bibliogr. 24 poz., rys., tab.
Twórcy
  • Lublin University of Technology, Department of Computer Science
  • Lublin University of Technology, Department of Computer Science
  • Lublin University of Technology, Department of Computer Science
  • University of Gdańsk, Faculty of Economics Department of Maritime Transport and Seaborne Trade
  • University of Gdańsk, Faculty of Economics Department of Maritime Transport and Seaborne Trade
Bibliografia
  • 1. Álvarez, J.F. (2009) Joint routing and deployment of a fl eet of container vessels. Maritime Economics & Logistics 11, pp. 186–208.
  • 2. Barrett, D. (2008) The off shore supply boat sector. Marine and Commerce February 2008, pp. 36–41.
  • 3. Brooks, M.R. & Button, K.J. (1994) Yield management: a phenomenon of the 1980s and 1990s. International Journal of Transport Economics 21(2), pp. 177–196.
  • 4. Brouer, B.D., Desaulniers, G. & Pisinger, D. (2014) A matheuristic for the liner shipping network design problem. Transportation Research Part E: Logistics and Transportation Review 72, pp. 42–59, doi: 10.1016/j.tre.2014.09. 012.
  • 5. Cariou, P. (2011) Is slow steaming a sustainable means of reducing CO2 emissions from container shipping? Transportation Research Part D: Transport and Environment 16(3), pp. 260–264, doi: 10.1016/j.trd.2010.12.005.
  • 6. Christiansen, M., Fagerholt, K., Nygreen, B. & Ronen, D. (2013) Ship routing and scheduling in the new millennium. European Journal of Operational Research 228(3), pp. 467–483, doi: 10.1016/j.ejor.2012.12.002.
  • 7. Czermański, E. (2019) Morska żegluga kontenerowa a zrównoważony rozwój transportu. Gdańsk: Wydawnictwo Uniwersytetu Gdańskiego Instytutu Transportu i Handlu Morskiego.
  • 8. Delgado, A. (2013) Models and algorithms for container vessel stowage optimization. Ph.D. thesis. IT University of Copenhagen.
  • 9. Erikstad, S.O. & Levander, K. (2012) System based design of offshore support vessels. IMDC12 – The 11th International Marine Design Conference, Glasgow UK, June 2012.
  • 10. Galor, W. (2013) Selected problems of optimal location of radar stations in the vessel traffic surveillance (VTS) system. Autobusy. Technika, Eksploatacja, Systemy Transportowe 3, p. 1525.
  • 11. Golias, M.M., Saharidis, G.K., Boile, M., Theofanis, S. & Ierapetritou, M.G. (2009) The berth allocation problem: optimising vessel arrival time. Maritime Economics & Logistics 11, pp. 358–377.
  • 12. Jensen, R.M. & Ajspur, M. L. (2022) Revenue management in liner shipping: Addressing the vessel capacity challenge. Maritime Transport Research 3, 100069, doi: 10.1016/j. martra.2022.100069.
  • 13. Kopacz, Z., Morgaś, W. & Urbański, J. (2007) European vessel traffic monitoring and information system. Zeszyty Naukowe Akademii Marynarki Wojennej 2(167), pp. 41–49.
  • 14. Maragos, S. (1994) Yield Management for Maritime Industry. Ph.D. thesis. Massachusetts Institute of Technology.
  • 15. Meng, Q., Wang, S., Andersson, H. & Thun, K. (2013) Containership routing and scheduling in liner shipping: overview and future research directions. Transportation Science 48(2), pp. 265–280.
  • 16. Mulder, J. & Dekker, R. (2014) Methods for strategic liner shipping network design. European Journal of Operational Research 235(2), pp. 367–377, doi: 10.1016/j. ejor.2013.09.041.
  • 17. Notteboom, T.E. (2006) The time factor in liner shipping services. Maritime Economics and Logistics 8(1), pp. 19–39.
  • 18. Oniszczuk-Jastrząbek, A., Czermański, E. & Kowalik J. (2021) The evolution of the fishing fleet and its energy demand. Scientific Journals of the Maritime University of Szczecin, Zeszyty Naukowe Akademii Morskiej w Szczecinie 68(140), pp. 57–65, doi: 10.17402/487.
  • 19. Pietrzykowski, Z. & Nozdrzykowski, Ł. (2013) Information and communication technologies in maritime transport – from information sharing toward service providing. TTS Technika Transportu Szynowego 20(10), pp. 3405–3414.
  • 20. Report shipping (2020) Managing Risk. Det Norske Veritas AS, Norwey.
  • 21. Song, D.-P. & Dong, J.-X. (2012) Cargo routing and empty container repositioning in multiple shipping service routes. Transportation Research Part B: Methodological 46(10), pp. 1556–1575, doi: 10.1016/j.trb.2012.08.003.
  • 22. Song, D.-P. & Dong, J.-X. (2012) Cargo routing and empty container repositioning in multiple shipping service routes. Transportation Research Part B: Methodological 46(10), pp. 1556–1575, doi: 10.1016/j.trb.2012.08.003.
  • 23. Ting, S.-C. & Tzeng, G.-H. (2004) An optimal containership slot allocation for liner shipping revenue management. Maritime Policy & Management 31(3), pp. 199–211.
  • 24. Wang, Y., Meng, Q. & Du, Y. (2015) Liner container seasonal shipping revenue management. Transportation Research Part B: Methodological 82, pp. 141–161, doi: 10.1016/j. trb.2015.10.003.
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2024).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-25a52b96-e912-4232-b1e4-e2855cee297a
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