Maritime transport is a pivotal logistics mode for the long-distance and bulk transportation of goods. However, the intricate planning involved in this mode is often hindered by uncertainties, including weather conditions, cargo diversity, and port dynamics, leading to increased costs. Consequently, accurately estimating vessel total (stay) time at port and potential delays becomes imperative for effective planning and scheduling in port operations. This study aims to develop a port operation solution with competitive prediction and classification capabilities for estimating vessel Total and Delay times. This research addresses a significant gap in port analysis models for vessel Stay and Delay times, offering a valuable contribution to the field of maritime logistics. The proposed solution is designed to assist decision-making in port environments and predict service delays. This is demonstrated through a case study on Brazil ports. Additionally, feature analysis is used to understand the key factors impacting maritime logistics, enhancing the overall understanding of the complexities involved in port operations.

翻译：海上运输是大宗货物长距离运输的关键物流模式。然而，该模式所涉及的复杂规划常受不确定性因素（包括天气条件、货物多样性及港口动态）制约，导致运营成本增加。因此，准确预估船舶在港总停留时间及潜在延误对于港口作业的有效规划与调度至关重要。本研究旨在开发一套具有竞争力的预测与分类能力的港口作业解决方案，以估算船舶总时长与延误时间。本研究填补了港口分析模型中船舶停留时间与延误时间研究的显著空白，为海事物流领域提供了重要贡献。该解决方案旨在辅助港口环境下的决策制定并预测服务延误，并通过巴西港口的案例研究进行验证。此外，采用特征分析以理解影响海事物流的关键因素，从而加深对港口作业复杂性的整体认知。