In 2013 the 10 largest container ports in the world accounted for 39.7% (i.e. 204m TEUs) of the total volumes handled by the world’s 100 leading container ports [10]. These mega-ports are responding to the ongoing vessel upsizing pursued by the container industry which is also embracing new alliance strategies in the attempt to return to sustainable profits by cutting down on operating costs. As a result, the container terminals working within these mega-ports are expected to comply with the corresponding need of productivity surge by adopting more flexible and effective infrastructures, equipment, policies and practices. Supposing that any further investment worth billions of dollars in new technology is currently to be ruled out, the most probable options for productivity raise in container terminals will likely rely on the integrated management of the internal logistic processes. Hence, the central role played by a proper decision support system (DSS) for operations integration and competitiveness becomes evident. In this paper we propose a model-driven DSS [30] for a real maritime container terminal devoted to pure transshipment. The terminal features human-operated equipment: rail mounted gantry cranes on the quay and a fleet of self-lifting shuttle vehicles called straddle carriers (SCs), where the latter provide for both container handling and transfer. The DSS is based on a specialized queuing-based modeling paradigm and it accounts for system infrastructure and human behavior under various sources of randomness. In particular, with respect to resource assignment and operational policies, the DSS is used to support decisions concerning i) the number of SCs to be assigned to each quay crane (QC) involved in container discharge/loading (D/L) operations, ii) the container deployment policy to be followed when stacking containers in the storage blocks on the yard and iii) the “best” path to be taken by the SC drivers according to the vehicle traffic they encounter along horizontal and vertical corridors and intersection points of the yard. Observe that after rubber-tired gantry cranes, SCs are the second most used material handling equipment (20.2%) in the storage yard [38]. So the core system of the DSS can be generalized and used in other container terminals as well.