The topic of the research is the development of new models and methods to assess the efficiency of port operations of sea passenger ports and terminals in order to effectively plan the work and accurate forecasting of infrastructure development. It is noted that changes in cruise and ferry route networks, especially relevant in the conditions of passenger traffic recovery after the gradual lifting of restrictions due to Covid-19, will directly affect port congestion. It is proposed to include into the sphere of decision-making on management of the sea passenger port the models based on consideration of probabilistic processes of cruise or ferry vessels calls. The Baltic Sea region is chosen as an object of research. The main modern directions in the sphere of sea passenger transportations confirming the gradual recovery of the route networks operation are presented. The flow of cruise and ferry vessels of the sea passenger port “Passenger port St. Petersburg “Marine Facade” is chosen as an object of research. The analysis of loading of berths, the analysis of the size of cruise and ferry ships, the route networks of ferry and cruise lines are carried out. As a result of the research a new stochastic model is presented and comparison with known distribution laws is carried out. Based on the data obtained, a confidence zone for making decisions on port congestion is determined. This area is formed on the basis of an assessment of the study of the dynamics of ship traffic nonstationary intensity, followed by the application of correlation-regression analysis and the characteristics of the random function describing the intervals between individual arrivals of cruise and ferry ships. The proposed model includes the ability to consider different priorities, primarily in terms of vessel length. Digital transport model is built in AnyLogic environment for port congestion study. The received data are used for optimization experiments in AnyLogic software environment with the purpose of complex estimation of the seaport operation for a year. Based on the optimization experiment and simulation, data are generated considering different distribution laws and used for decision making in case of uncertainty for infrastructure modernization. The presented model can be used for substantiation of management decisions both on strategic and tactical levels for assessing the efficiency of investment projects on development of sea passenger ports and terminals.
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