The Impacts of the Applications of Artificial Intelligence in Maritime Logistics

Abstract

This study aims to identify current approaches in the usage of Artificial Intelligence (AI) methods for solving shipping problems. Recent advances in AI are being examined, and the way it is adapted to maritime logistics is reviewed. In this study, 66 papers dealing with AI in the maritime industry are reviewed bibliometrically. Research data were primarily sourced from databases of IEEE Xplore, Web of Science, ScienceDirect (Elsevier), Sciences Citation Index, Google Scholar, Springer, and journals. Selected papers are categorized and classified, and the outcomes of some noteworthy publications are discussed in detail. A comprehensive assessment is also presented, which highlights research gaps and forecasts future research orientations. Two possible areas in the maritime industry are proposed for further research using AI capabilities. Predictive analysis is the first domain, followed by energy efficiency optimization. In addition, Machine Learning (ML) and Operations Research (OR) have fostered a growing interest in automating the learning of heuristics to solve optimization problems to avoid the need for expensive and inefficient human labour to create highly specialized heuristics. Future research can take advantage of these new ML approaches to address Maritime Logistics problems utilizing the ever-increasing amount of data available. Future research on maritime logistics can also develop learning models based on the identified gaps.