  The DEBS Grand Challenge 2018 is set in the context of maritime route
prediction. Vessel routes are modeled as streams of Automatic Identification
System (AIS) data points selected from real-world tracking data. The challenge
requires to correctly estimate the destination ports and arrival times of
vessel trips, as early as possible. Our proposed solution partitions the
training vessel routes by reported destination port and uses a nearest neighbor
search to find the training routes that are closer to the query AIS point.
Particular improvements have been included as well, such as a way to avoid
changing the predicted ports frequently within one query route and automating
the parameters tuning by the use of a genetic algorithm. This leads to
significant improvements on the final score.
