Intermodal terminals are important facilities in the container transport network, providing an exchange of containers between road and rail transport. Numerous factors can affect throughput in such highly integrated systems. These include numbers and types of equipment, physical layout, storage capacity and operating strategies. This study aims to improve operating strategies by developing an analytical tool to assist in load planning of container trains. The problem investigated can be described as a dynamic assignment problem with many uncertain parameters. Numerical investigations focus on tuning the proposed model to deal with the uncertainties. ᭧

Abstract. This paper considers one important aspect of operations planning referred to hereafter as train planning. Train planning is the process of spatially assigning containers to specific wagons (also known as railcars) on an intermodal train. The spatial arrangement of containers on a train can have a significant influence over the amount of time and energy consumed in the handling of containers. Efficient train planning can also maximise utilisation of wagon carrying capacity. This study proposes a mixed-integer programming model to determine the arrangement of containers on a train to minimise a weighted sum of number of wagons required and equipment working time. Due to the large number of variables, the proposed model cannot be solved in a timely manner for practical problems. This is addressed by applying heuristic algorithms local search and simulated annealing.Discrete-event simulation of an intermodal terminal is used to evaluate the proposed methods and to illuminate various properties of the model.

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