Molslinjen saves fuel and enhances guest experience with artificial intelligence

Since 2019, Molslinjen has been collaborating with the AI company Halfspace to make the shipping company a data-driven one. Algorithms and artificial intelligence assist in predicting the number of passengers and vehicles expected on each departure. This enables Molslinjen to better adjust their loading, pricing, and crew.

The reason for the implementation can be found in the need to optimize ferry packing. Typically, one does not know until the last moment how many cars will actually be on board.

It's like playing Tetris, and if you know in advance which shapes are coming, you're better off

— says Jesper Skovgaard, Commercial Director at Molslinjen.

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Technology aids in fuel savings and improves guest experience

Algorithms and pattern recognition are among the technologies Molslinjen uses. They help predict how many travelers will be present leading up to a departure time. This helps reduce unnecessary waiting time at the ferry terminal and, notably, reduces ferry fuel consumption, which has decreased by three percent through better departure planning, says Jesper Skovgaard:

This means that we depart faster, have shorter port stays, we don't have to make up for delays, and we save a significant amount of oil

— says the Commercial Director, who also points to the new ferry terminal at the port area of Aarhus as part of the explanation for a better guest experience:

"The better prepared we are for each departure - the better we can load the ferry and depart on time. When sailing with ferries, timeliness is something we emphasize greatly. Our new ferry terminal in Aarhus is equipped with long, straight ramps, making it easier for us to start loading the right way - and thus it also becomes easier to finish correctly. This means concretely that we can better create space on the most attractive departures, which may have previously just been sold out."

The collaboration between Molslinjen and Halfspace has been selected as a finalist in the Franz Edelman Award, a prestigious competition in operations research, analytics, and management science.