Integrated Rescheduling for Vessels and Tugboats in One-Way Channel Ports Under Adverse Weather Conditions
To address the significant operational disruptions caused by inclement weather in maritime logistics, this study investigates the integrated rescheduling optimization of vessels and tugboats within one-way channel ports. The research aims to minimize total operational costs, including dispatching and delay penalties, by synchronizing vessel movements with tugboat service capabilities under uncertain conditions. Methodologically, a rolling horizon decision-making mechanism is proposed to accommodate dynamic operational scenarios driven by fluctuating weather. On this basis, an integrated rescheduling model is developed to address the compounded challenges of navigation rule changes, channel closures, vessel delays, and additional shifting tasks. The model explicitly incorporates critical constraints such as channel navigation protocols, tugboat availability, power capacity limits, and tidal windows for deep-draft vessels. To achieve efficient solution generation, an improved Variable Neighborhood Search (VNS) algorithm is designed to effectively handle the problem’s complexity. Experimental results validate the effectiveness of the proposed approach and the robustness of the algorithm in diverse disruption scenarios. Furthermore, sensitivity analyses reveal how channel closure duration, vessel delay intensities, and the volume of shifting tasks quantitatively influence rescheduling outcomes. This study contributes a novel synergistic optimization framework that enhances the operational resilience and decision-making capabilities of port authorities.
Authors
- Shiyan Jia
- Hongxing Zheng
Institutions
- Dalian Maritime University (CN)
Publication Details
- Journal
- Journal of Marine Science and Engineering
- Published
- 2026-03-09
- DOI
- https://doi.org/10.3390/jmse14050512
- Primary Topic
- Maritime Transport Emissions and Efficiency
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China