Optimizing container terminal operations: a systematic review of operations research applications

Operations research techniques have helped optimize container terminal operations over the past decades and have been a regular feature of maritime logistics and maritime supply chain literature in addition to being in practice at container terminals across the globe. Our systematic review collated through Scopus, 1768 papers published in the domain and analyzed them to find the main research clusters, and explore future research directions. Studies on both quayside and landside planning are grouped in five research clusters: discussing simulation, scheduling, automation, quayside operations, integrated operations and container transportation. In addition, the evolution of optimization techniques in planning container terminal operations is discussed, along with the suggested trajectory of the research agenda under each cluster. The analysis finds that genetic algorithms, integer linear programming and heuristics are the most widely used operations research techniques in container terminal optimization. While clusters of research in areas such as simulating container terminal operations, scheduling operations and automated terminals have received a great deal of attention, research focusing on integrated and dynamic operations has been scarce over the past years, suggesting a new area of contributions. The review proposes the application of methods such as neural network- and deep learning models related to artificial intelligence to widen our understanding of container terminal operations.