Port Operation

Port operation research focuses on optimizing efficiency, sustainability, and security within port environments. Current research emphasizes data-driven approaches, employing machine learning (including models like LSTM autoencoders and particle swarm optimization) and digital twin technologies to improve scheduling, predict vessel delays, detect anomalies (e.g., oil spills), and enhance overall port management. These advancements aim to reduce operational costs, minimize environmental impact, and improve safety through more efficient resource allocation and predictive analytics.