In a context of private operators competing for the same infrastructure, digitalisation is essential to support public entities in decision-making processes to ensure both fairness and efficiency when managing transport systems. This contribution presents the methods and instruments which have been integrated to face such task in the Port of Trieste, which is the first Italian port for throughput and rail movements. According to the proposed approach, railway transport processes have been first modelled through a standardized modelling language to facilitate the analysis of the operational model and the identification of possible bottlenecks. Then, graphical models have been parametrized to serve process simulation, which has been carried out by means of a discrete-event simulation engine. This latter has represented the black box of a multi-disciplinary optimization framework implementing genetic algorithms, which enabled to compute the optimal port railway capacity on varying of the destination sequence of arriving trains. Further optimization runs have been performed maximising also the capacity of the most potentially critical terminal in terms of traffic volumes, in order to evaluate the consequences on the productivity of the remaining terminals. Finally, obtained outcomes have been gathered into a database and visualized using a parallel coordinates plot, which displays the capacity of the entire port railway system and of every individual terminal as the numerical variables under investigation. Thanks to this resulting chart, authorities in the Port of Trieste now dispose of an effective digital tool to estimate changes in railway capacity at terminal and port level, and to assess the system responsiveness by comparing optimized values with expected trends. The successful application of the adopted methodology to a real-word case study demonstrates its validity and suggests its transferability to other freight transport and logistics issues and environments, fostering the use of digitalisation to make more informed decisions.

Port railway capacity; Multi-objective optimization; Decision-making support