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Forecasting of the route network of ferry and cruise lines based on simulation and intelligent transport systems

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
According to statistics, the marine passenger transportation sectors (both cruise lines and ferry lines) show a significant increase of passenger traffic and the intensity of ship routes. But new features of the conditions for passenger traffic growth require the development of new methodological transport models for cruise and ferry networks and new practical forecasting methods. Changes are observed in the fleet composition, mostly in the direction of increased. New approach for forecasting has to be based on the interaction of such systems as ≪city‒sea passenger port‒cruise and ferry lines. This condition now determines new need to describe the principles and forms of organization of maritime ferry networks and changes under the influence of the external environment. The object of the research is the Baltic Sea region and the existing route networks of cruise and ferry lines. Exploring this system, the usage of new mathematical apparatus based on correspondence matrices and agent-based simulation was justified for estimating the workload on transport infrastructure around the passenger port and for the existing ferry or cruise route network. The practical results of new simulation model, on the one hand, justify the need for a comprehensive study of the conditions for the formation of ferry and cruise route networks in changing conditions. On the other hand, these new results could improve the quality of decision-making process in forecasting the route network on the basis of the research of passenger traffic between systems city‒sea terminal-cruise line or ferry line.
Czasopismo
Rocznik
Strony
111--121
Opis fizyczny
Bibliogr. 17 poz.
Twórcy
  • Saint-Petersburg State University of Aerospace Instrumentation 67, Bolshaya Morskaia, Saint-Petersburg, 190000, Russia
  • Saint-Petersburg State University of Aerospace Instrumentation 67, Bolshaya Morskaia, Saint-Petersburg, 190000, Russia
  • University of Dubrovnik, Electrical Engineering and Computing Department Cira Carica 4, 20 000 Dubrovnik, Croatia
  • University of Dubrovnik, Electrical Engineering and Computing Department Cira Carica 4, 20 000 Dubrovnik, Croatia
Bibliografia
  • 1. CINN 2018 EUROPE. European Cruise Lines.Available at: https://www.cruiseindustrynews.com.
  • 2. Vaya, E. & Garcia, J. & Murillo, J. & Romani, J. & Surinach, J. Economic Impact of Cruise Activity: The Port of Barcelona. 2016. 30 p.
  • 3. Wright, A. Unctad monographs on port management. The economic impact of cruise ports: The case of Miami. New York and Geneva. 2001. 33 p.
  • 4. Service Marinetraffic. Available at: https://marinetraffic.com.
  • 5. Mulder, J. & Dekker, R. Methods for strategic liner shipping network design. European Journal of Operational Research. 2014.Vol. 235(2). P. 367-377.
  • 6. Dong, J.X. & Lee, C.Y. & Song, D.P. Joint service capacity planning and dynamic container routing in shipping network with uncertain demands. Transportation Research Part B Methodological. 2015. Vol. 78. P. 404-421.
  • 7. Aversa, R. & Botter, R.C. & Haralambides, H.E. & Yoshizaki, H.T.Y. A mixed integer programming model on the location of a hub port in the east coast of South America. Maritime Economics & Logistics. 2005. Vol. 7(1). P. 1-18.
  • 8. Krile, S. Efficient Heuristic for Non-linear Transportation Problem on the Route with Multiple Ports. Polish Maritime Research. Gdansk. Poland. 2013. Vol. 20. No. 4. P. 80-86. DOI: 10.2478/pomr-2013-0044. https://doi.org/10.2478/pomr-2013-0044
  • 9. Baltic Sea Sewage Port Reception Facilities 2018. Baltic Marine Environment Protection Commission. Available at: http://www.helcom.fi.
  • 10. Cruise Information Agency CRUISEINFORM.RU. Available at: http://www.cruiseinform.ru/news/morskie_kruizy/1402201/.
  • 11. Patric, S. & Marcus, N. Alternative solutions for terminal traffic. Goteborg. Sweden. 2006. 83 p.
  • 12. Krile, S. & Maiorov, N. & Fetisov, V. Forecasting the operational activities of the sea passenger terminal using intelligent technologies. Transport Problems. 2018. Vol. 13. No. 1. P. 27-37.
  • 13. Фетисов, В. & Майоров, Н. Практические задачи моделирования транспортных систем. Санкт-Петербург: ГУАП. 2012. 185 p. [In Russian: Fetisov, V. & Maiorov, N. Practical Problems of Modeling of Transport Systems. Saint-Petersburg: SUAI].
  • 14. Naumova, N. & Danovich, L. A model of flows distribution in the network. Life Science Journal. 2014. No. 11(6). P. 591-597.
  • 15. Zhou, X. & Qin, X., & Mahmassani, H.S. Dynamic origin–destination demand estimation using multiday link traffic counts for planning applications. Transportation Research Record. 2003. No. 1831. Р. 30-38.
  • 16. Barron, P. & Greenwood, A.B. Issues determining the development of cruise itineraries: a focus on the luxury market. Tourism in Marine Environments. 2006. Vol. 3(2). P. 89-100.
  • 17. Gui, L. & Russo, A.P. Cruise ports: a strategic nexus between regions and global lines – evidencerom the Mediterranean. Maritime Policy & Management. 2011. Vol. 38(2). P. 129-150.
Uwagi
PL
Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-d854d1fa-ee5a-4cc4-b79d-eee43ddc6407
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