Preview

Vestnik Gosudarstvennogo universiteta morskogo i rechnogo flota imeni admirala S. O. Makarova

Advanced search

Research of Berth Occupancy at a Sea Passenger Port Based on a Simulation Model Accounting for Regional Features and Stochastic External Influences

https://doi.org/10.21821/2309-5180-2025-17-6-801-815

EDN: CFLCLU

Abstract

The article addresses the topical problem of forming big data to support decision-making and forecasting the development of maritime passenger ports based on data obtained from a digital twin of a seaport, taking into account regional features. Maritime passenger ports and terminals of the Baltic Sea were selected as the object of study. The necessity of multi-scenario modeling of varying intensities of cruise and ferry vessel calls is substantiated, with consideration given to berth characteristics, operational constraints, and decision-making limitations when processing navigation-period data. To address this problem, a new digital transport model is proposed that enables effective analysis and optimization of cruise and ferry vessel servicing processes. An algorithm and a novel approach to the analysis of fixed and stochastic inbound vessel flows are developed, taking into account service priority. The study employs multi-scenario simulation methods based on different traffic intensities and regional characteristics of port infrastructure. The research is based on an analysis of real operational data from Baltic Sea passenger ports, which allows evaluation of the proposed model under conditions of maximum port load, using the ports of Warnemünde (Rostock) and Kiel as case studies. Special attention is given to the analysis of port infrastructure utilization intensity and optimization of resource allocation. A simulation model is presented to represent the operation of a multi-priority queueing system in which service requests arrive both according to a priority schedule and randomly. The boundary operating conditions of two Baltic Sea passenger ports for accommodating vessel calls beyond the planned schedule under stochastic influences are experimentally determined. The modeling is based on actual port infrastructure data and planned cruise ship arrival schedules. The proposed software module of the digital port model enables the generation of simulation data to support both operational management decision-making at maritime passenger ports and long-term development forecasting.

About the Authors

N. N. Maiorov
Saint-Petersburg State University of Aerospace Instrumentation
Russian Federation

Maiorov, Nikolai N. — Grand PhD in Technical Sciences, Associate Professor

 67/A Bol’shaya Morskaya Str., St. Petersburg, 190000



V. A. Fetisov
Saint-Petersburg State University of Aerospace Instrumentation
Russian Federation

Fetisov, Vladimir A. — Grand PhD in Technical Sciences, Professor

67/A Bol’shaya Morskaya Str., St. Petersburg, 190000



M. R Yazvenko
Saint-Petersburg State University of Aerospace Instrumentation SUAI
Russian Federation

Yazvenko Maksim Romanovich — Postgraduate Student

67, Bolshaya Morskaia str., Saint-Petersburg, 190000



References

1. Krile, S. and N. Maiorov. “The influence of external environment to the ferry lines and marine passenger terminals.” Transport Problems 15.4 part 2 (2020): 203–214.

2. G. Ćorluka, I. Peronja and D. Tubić. “Cruise Port Passenger Flow Analysis: a Cruise Port Governance Perspective.” Naše more 67.3 (2020): 181–191. DOI: 10.17818/nm/2020/3.1.

3. Yazvenko, M. R. “Universal simulation model of cruise and ferry ships flow to a sea passenger port.” Vestnik gosudarstvennogo universiteta morskogo i rechnogo flota im. admirala S. O. Makarova 17.3 (2025): 350–364. DOI: 10.21821/2309-5180-2025-17-3-350-364.

4. London, W. R. and G. Lohmann. “Power in the context of cruise destination stakeholders’ interrelationships.” Research in Transportation Business & Management 13 (2014): 24–35. DOI: 10.1016/j.rtbm.2014.11.004.

5. Dorigatti, J., T. Perić and G. J. Mrčelić. “Cruise Industry Trends and Cruise Ships’ Navigational Practices in the Central and South Part of the Adriatic East Coast Affecting Navigational Safety and Sustainable Development.” Applied Sciences 12.14 (2022). DOI: 10.3390/app12146884.

6. Brodetskiy, G. L. Systemniy analiz i logistica. Priniatie resheniy v usloviiakh neopredelennosti. M.: Academia, 2010: 336.

7. Andreeva, L. A., A. L. Kuznetsov, A. M. Sampiev and A. D. Semenov. “Tasks of improving methods of technological design of trade sea ports in new conditions.” Transport Business of Russia 1 (2024): 164–166.

8. Marcussen, C. H. “Visualising the network of cruise destinations in the Baltic Sea — a multidimensional scaling approach.” Scandinavian Journal of Hospitality and Tourism 17.2 (2017): 208–222. DOI: 10.1080/1502225 0.2016.1142893.

9. Rusinov, I. A. “Primenenie teorii massovogo obsluzhivaniya dlya otsenki propusknoy sposobnosti spetsializirovannykh terminalov.” Ekspluatatsiya morskogo transporta 3(57) (2009): 3–5.

10. Yazvenko, M. R. “Research of berths utilization at sea passenger port on the basis of modeling.” System Analysis and Logistics 2(28) (2021): 104–113. DOI: 10.31799/2077-5687-2021-2-104-113.

11. Kitikov, A. N., A. L. Kuznetsov and I. A. Rusinov. “Limitation of the queuing theory techniquesfor the assessment of sea port front.” Ekspluatatsiya morskogo transporta 1(71) (2013): 3–6.

12. Kuznetsov, A. L., A. V. Galin and G. B. Popov. “Discrete-event modelling of container terminal cargo fronts.” Vestnik gosudarstvennogo universiteta morskogo i rechnogo flota im. admirala S. O. Makarova 15.4 (2023): 589–602. DOI: 10.21821/2309-5180-2023-15-4-589-602.

13. Mayorov, N. N. and V. A. Fetisov. “Research of operational processes passenger services in the marine passenger terminal using simulation.” Vestnik gosudarstvennogo universiteta morskogo i rechnogo flota im. admirala S. O. Makarova 6(40) (2016): 70–80. DOI: 10.21821/2309-5180-2016-8-6-70-80.

14. Katalevsky, D. Yu. Osnovy imitacionnogo modelirovaniya i sistemnogo analiza v upravlenii M.: Izdatel’skij dom «Delo»: RANHiGS, 2015.

15. Jaiswal, N. K Priority Queues Mathematics in science and engineering; v. 50. New York, Academic Press, 1968: 240.

16. A Dobrovolskaia, N. N. Maiorov, M. R. Yazvenko, “Decision-making under uncertainty in forecasting the evelopment of a sea passenger port based on the modeling of different priorities of ships” Wave electronics and infocommunication systems: Proceedings of the XXVI International Scientific Conference. Volume 3, Saint-Petersburg, Saint-Petersburg State University of Aerospace Instrumentation, 2023. — p. 107–112.

17. Mayorov, N. N. and M. R. Yazvenko. “Research and development of an information modification system for multi-priority streams.” Metrologicheskoe obespechenie innovatsionnykh tekhnologiy: Sbornik statey VII Mezhdunarodnogo foruma, Sankt-Peterburg, 04 marta 2025 goda. Sankt-Peterburg: Sankt-Peterburgskiy gosudarstvennyy universitet aerokosmicheskogo priborostroeniya, 2025: 204–205.

18. Maiorov, N. N. and M. R. Yazvenko. “Research and Development of an Algorithm for Multi-Priority Flows in Transportation Systems.” 2024 Wave Electronics and its Application in Information and Telecommunication Systems (WECONF) — 2024: 1–4. DOI: 10.1109/WECONF61770.2024.10564652.

19. Kleinrock, Leonard. Queueing Systems, Volume 1: Theory. New York: John Wiley & Sons, 1975.

20. Our Terminals — PORT OF KIEL. Web. 1 October 2025 <https://www.portofkiel.com/harbours-terminals.html>.

21. Rostock Port: Portplan. Web. 1 October 2025 <https://www.rostock-port.de/en/habour-plan>.


Review

For citations:


Maiorov N.N., Fetisov V.A., Yazvenko M.R. Research of Berth Occupancy at a Sea Passenger Port Based on a Simulation Model Accounting for Regional Features and Stochastic External Influences. Vestnik Gosudarstvennogo universiteta morskogo i rechnogo flota imeni admirala S. O. Makarova. 2025;17(6):801-815. (In Russ.) https://doi.org/10.21821/2309-5180-2025-17-6-801-815. EDN: CFLCLU

Views: 17

JATS XML


Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.


ISSN 2309-5180 (Print)
ISSN 2500-0551 (Online)