Xiang Hong, Wang Lumin, Ji Shouwen, Guo Jiaqi, Jiang Mingyue. Ship scheduling optimization in the river-sea intermodal interface area of the Pinglu canalJ. Navigation of China, 2026, 49(3): 141-151. DOI: 10.3969/j.issn.1000-4653.2026.03.015
    Citation: Xiang Hong, Wang Lumin, Ji Shouwen, Guo Jiaqi, Jiang Mingyue. Ship scheduling optimization in the river-sea intermodal interface area of the Pinglu canalJ. Navigation of China, 2026, 49(3): 141-151. DOI: 10.3969/j.issn.1000-4653.2026.03.015

    Ship scheduling optimization in the river-sea intermodal interface area of the Pinglu canal

    • With the advancement of the Pinglu Canal project,the navigational environment in the Legou Operation Area of Qinzhou Port,which serves as a river-sea intermodal interface area,has become increasingly complex. The vessel traffic density has also increased significantly,posing challenges to the efficiency and safety of ship scheduling. Existing scheduling methods still have limitations in conflict resolution and coordinated optimization when facing diverse vessel traffic conflicts in this area,making it difficult to effectively address the core engineering problem of low navigational efficiency combined with potential safety hazards. To solve this problem,this study proposes a multi-objective ship scheduling optimization model and solution method integrating traffic conflict resolution. First,based on an in-depth analysis of the navigational characteristics of the interface area,the main traffic conflict types,including overtaking,head-on,and crossing conflicts,are identified and classified. Second,a multi-objective mixed-integer programming model is developed to minimize the total scheduling time and total waiting time of ships,while incorporating multiple constraints such as traffic conflict resolution and berth allocation. Given the characteristics of the model,an improved Differential Evolution-Non-dominated Sorting Genetic Algorithm II (DE-NSGA-II) is designed. By employing five-dimensional chromosome encoding and a hierarchical evolutionary strategy,the proposed algorithm improves search efficiency and solution quality in a complex constrained space. The proposed method is validated through simulation experiments under representative navigational scenarios,and comparative analyses are conducted against the traditional First-Come-First-Served (FCFS) strategy. The results show that the proposed method performs well in terms of convergence and constraint satisfaction and can significantly reduce ship scheduling time. The optimization effect becomes more pronounced as the number of ships increases,providing a feasible technical approach for improving vessel traffic efficiency and scheduling management in complex river-sea intermodal interface areas.
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