5. Conclusions
Decisions on the integrated management of container handling operations in a maritime container terminal stem from a real environment where events and logistic activities occur at random. So, the terminal manager asks for a proper supporting model to quantify the effects of randomness upon an efficient integrated management. We have shown that the quay crane blocking and starvation phenomena during container discharge/loading, as well as the vehicle interaction during internal container transfer and, finally, the yard row locking policy in the storage area can be captured by a queuing network model. This has been put at the basis of the development of a (queuing) model-driven DSS. Once that the difficulty of pursuing any practical analytical solution of the driving queuing network has been discussed, solution efforts have been steered towards the use of discrete-event simulation.
The proposed DSS has been conceived to support operations management at a generic container terminal of pure transshipment equipped with self-lifting shuttle vehicles. DSS capability in representing with great detail the trips of the self-lifting shuttle vehicles devoted to container handling and transfer between the quay and yard has been successfully validated and put at work in the transshipment hub located at the port of Gioia Tauro in Italy.
