Going Green with AI An Innovative Look into Intermodal Rail



Alex Van Winckel, Dr. Eva Savelsberg, and Matthew Wittemeier, INFORM, Aachen, Germany


Artificial Intelligence (AI) is seemingly popping up everywhere these days. As a niche AI system provider, INFORM has been delivering AI solutions for just over two decades, and we have found that within the maritime sector, optimization modules deliver value across terminals. This is because as decision-making is improved, efficiency is realized across the terminal in both the short- and long-term. Short-term savings often translate directly to the bottom line. Efficiencies such as reductions in vehicle travel, crane travel, and yard re-handles are the easiest to see and calculate. Long-term savings, as well as potential revenue increases, can be harder to see initially, however.

Reductions in overall handling equipment as well as delaying or avoiding new equipment purchases happen slowly as operators adjust operational procedures to maximize the efficiency gains possible. Furthermore, increasing yard, truck, and rail handling capacities are intangible results that are the byproducts of more efficient terminals. All of these long-term outcomes deliver significant value, and through these activities, there are also strong environmental sustainability outcomes that can be achieved simultaneously. This paper focuses on one optimization module, INFORM’s Train Load Optimizer, and forms a case study for how strong optimization can deliver cost savings while also improving environmental performance.

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