A Systematic Literature Review of Machine Learning Applications for Port's Operations

In transportation systems, there is a need of Machine Learning (ML) to create intelligent solutions for many issues. In port's studies, there has been a long focus on optimization and simulation modeling, but still, ML served in building more complex decision support systems for better management of port operations. To evaluate the contributions in the application of ML for port operations, we conducted this Systematic Literature Review (SLR) in order to select and characterize the most relevant papers. This paper, reports the applied research protocol and its results, and highlights the gaps that could be addressed in future works.