Minimizing RMG Reshuffling through Preventive Yard Optimization. A Data-Driven Simulation-Base Approach

Optimizing container handling operations in the yards is a key factor in improving terminal performance and minimizing environmental impact. This study presents a simulation-based framework for the evaluation of a priority-driven unloading strategy using rail mounted gantry cranes for loading containers onto trains for their inland forwarding. A simulation model, developed in Witness Horizon, first reproduces the import flow and allows the collection of data on system performance. Then, a hill-climbing algorithm implemented in Matlab, performs an advanced reorganization of the yard, with the aim of identifying an initial configuration of the railyard that reduces the number of remarshalling operations required. The proposed approach integrates container delivery priorities with controlled reallocation procedures, while incorporating the spatial and visibility constraints observed in real operations. The proposed integrated simulation - optimization framework, tested according to the practices of the PSA Pra' terminal in Genoa, serves both as a decision support tool and as a basis for testing site management strategies under realistic conditions. The results show how the integration of simulation and local optimization can provide effective decision support for terminal management.