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An integrated queueing network focused on container storage/retrieval operations occurring on the yard of a transshipment hub is proposed. The purpose of the network is to support decisions related to the organization of the yard area, while also accounting for operations policies and times on the quay.

A discrete-event simulation model is used to reproduce container handling on both the quay and yard areas, along with the transfer operations between the two. The resulting times, properly estimated by the simulation output, are fed to a simpler queueing network amenable to solution via algorithms based on mean value analysis (MVA) for product-form networks.

Numerical results justify the proposed approach for getting a fast, yet accurate analytical solution that allows carrying out performance evaluation with respect to both organizational policies and operations management on the yard area.

Practically, the expected performance measures on the yard subsystem can be obtained avoiding additional time-expensive simulation experiments on the entire detailed model.

As a major takeaway, deepening the MVA for generally distributed service times has proven to produce reliable estimations on expected values for both user- and system-oriented performance metrics.

The use of queueing network models was stimulated by the appearance (1975) of the exact product form solution of a class of open, closed and mixed queueing networks obeying the local balance principle and solved, a few years later, by the popular mean value analysis algorithm (1980). Since then, research efforts have been produced to approximate solutions for non-exponential services and non-pure random mechanisms in customer processing and routing. The purpose of this paper is to examine the suitability of modeling choices and solution approaches consolidated in other domains with respect to two key logistic processes in container terminals.

In particular, the analytical solution of queueing networks is assessed for the vessel arrival-departure process and the container internal transfer process with respect to a real terminal of pure transshipment.

Numerical experiments show the extent to which a decomposition-based approximation, under fixed or state-dependent arrival rates, may be suitable for the approximate analysis of the queueing network models.

The limitation of adopting exponential service time distributions and Poisson flows is highlighted.

Comparisons with a simulation-based solution deliver numerical evidence on the companion use of simulation in the daily practice of managing operations in a finite-time horizon under complex policies.

Discussion of some open modeling issues and encouraging results provide some guidelines on future research efforts and/or suitable adaption to container terminal logistics of the large body of techniques and algorithms available nowadays for supporting long-run decisions.