Optimal capacity planning for general cargo terminals with data-driven discrete event simulation

Abstract

Different from container ports, general cargo terminals have a large variety of cargo types but small amount for each type. It is critical to analyze the performance of the general cargo terminals considering the scarcity of dedicated resources for each cargo category. However, to build an analytical or conventional simulation model for the terminals can be difficult, especially when many non-standardized procedures are involved. Such difficulties restrict the ability to evaluate and optimize the performances of the terminals. In this study, we developed a data-driven discrete event simulation model using the O2DES framework, for evaluating the performance of general cargo terminals. Subsequently, we illustrate four different base strategies that would potentially increase the capacity of the terminals. Moreover, to identify the optimal combined strategy in an efficient manner, we develop an algorithm with simulation allocation rule based on the concept of Optimal Computing Budget Allocation (OCBA). The approaches are tested and validated based on the historical data and domain inputs of a given set of general cargo terminals at one of the largest multi-purpose port in Southeast Asia. Nevertheless, the proposed techniques are general, which can be extended for application on different cargo types and port configurations.