The volume of containerized cargo traffic has increased steadily over the last three decades. Because of significant cost advantages on long-haul trips and growing concern for the environment, large portions of this traffic are now transported by trains rather than trucks. The main stumbling block that has prevented rail transportation from playing an even more prominent role in the movement of containerized cargo has been the cost of transferring containers between vessels and trains. This research explores innovative systems capable of performing such transfer operations efficiently.
Terminals with rail tracks along the docks – allowing for trains to be loaded directly from ships – are common for bulk cargo, but have not to date been implemented successfully for containerized cargo. The main reasons for this are: (i) the need to classify trains by container destination, and (ii) the reduced dock crane throughput resulting form interference among multiple cranes unloading containers onto a single rail track.
The main thrust of this research is the development of a direct-transfer terminal design that allows trains to be loaded and simultaneously classified by destination, largely eliminating the need for further train processing at downstream rail yards.
Analytical methods are developed to evaluate the performance of the proposed design, including train classification levels attainable during the loading process and the productivity of the dock system. The methods are validated against a computer simulation.
A comprehensive economic model is developed to measure the costs incurred while moving containers through the proposed terminal and through conventional facilities. The model includes factors that are often neglected in the literature, such as container inventory costs.
Several operating scenarios are used to identify the conditions under which each type of terminal design is most effective. The results show that direct-transfer terminals can be more cost-effective intermodal. The savings are mainly due to reduced handling and inventory costs, but the approach also has environmental advantages and lends itself very well to automation.