Ship Scheduling for Taicang Port

Taicang Port, as one of the largest inland ports in China, has a large number of arriving ships. Because of the geographical location, Taicang Port’s shipping channels are narrow, and these channels are often busy with ship traffic. Thus, the large number of ships arriving at the container terminal of Taicang Port have to be appropriately scheduled to avoid channel congestion. However, the traditional method of scheduling manually and the fluctuating number of ships increase the difficulty of ship scheduling in Taicang Port. We propose a mixed-integer programming model and design a customized adaptive large neighborhood search algorithm to address the complex ship-scheduling problem. The realistic constraints, including practical ship-scheduling priorities and berthing rules, are considered in our formulated model. The algorithm solutions in various instances are compared with GUROBI as benchmarks to demonstrate the effectiveness of our proposed approach. We also compare the algorithm solutions with the traditional manual scheduling results in terms of ship waiting times and numbers of uncompleted ships. Furthermore, we develop an intelligent ship scheduling system for Taicang Port that significantly improves the efficiency of ship scheduling. It can be quantified as a revenue increase of about $5.66 million in one year. The system has been applied in Suzhou Modern Terminal of Taicang Port as a pilot unit, where it could save about $0.512 million in labor and loss costs a year. Through our developed system, the container terminal realizes the visualization of ship-scheduling operations and centralized management of ship arrangement data. Furthermore, the Taicang Port Administrative Committee, as managers, can easily access the ship-scheduling system to view and supervise specific operations.

History: This paper was refereed.

Funding: This research was supported by the National Natural Science Foundation of China [Grants 72025103, 72394360, 72394362, and 72361137001] and the Project of Science and Technology Commission of Shanghai Municipality China [Grant 23JC1402200].