A decision support tool based on a queueing model for performance analysis and optimization of container terminals

The constant growth of container traffic has posed the problem of devising efficient tools for the management of logistics activities at container terminals, where a number of tasks are carried out, including loading, unloading and storing. To this purpose, a decision support system (DSS) based on a discrete-time dynamic model of container flows in maritime terminals is proposed for performance analysis and simulation. The tool can be used both for planning and real-time decision support in the management of the handling resources. More specifically, on the one hand, it is possible to evaluate the performance of a container terminal (in terms of different indexes of interest) and the improvements attainable by possible changes in the resources (for example, to understand the impact of adding or removing a crane) in various scenarios. On the other hand, the DSS is also able to compute a real-time strategy of resource allocation aimed at optimizing the overall efficiency of the operations dynamically. The model at the core of the DSS has control inputs that represent the percentages of capacities of the available handling machines used to move containers inside a terminal. We regard such capacities as limited resources to be allocated to the various operations they are required for. By suitably choosing different cost functions, it is possible to address various optimization problems that can take into account different performance indexes. The model is based on a discrete-time state equation that describes the dynamic behaviour of the quantities of containers stored or transferred across a maritime terminal. It is basically a system of queues that represent either temporal storages or delays that may occur during the container transfers due to the unavailability of resources. The proposed tool integrates simulation and optimization in an easy-to-use fashion, thus making it useful also for those with no experience in simulation. An example of the possible uses of the tool is reported to show its effectiveness in evaluation of the terminal performance. The paper is structured as follows: Section 1 concerns introduction; Section 2 describes the main features of the tool, specifically for performance analysis and container flow optimization; Section 3 contains a simulation case study that shows possible uses of the DSS; Section 4 illustrates the basic ideas of the dynamic model of the container flows that is the basis of the proposed DSS; finally, Section 5 addresses conclusions and further comments.