Effective use of port waterways is conducive to enhancing port competitiveness. To minimize the waiting time of ships, improve traffic efficiency, and enhance the applicability of the model to the presence of uncertain factors, a fuzzy scheduling optimization method for ships suitable for one-way waterways is proposed based on fuzzy theory. Considering the ambiguity of the speed of ships entering and exiting the port or the time it takes to cross the channel, the previous research on vessel scheduling on one-way waterways has been extended by introducing a triangular fuzzy number and a method for determining the feasible navigable time window of a ship subject to the tide height constraint was proposed. In this study, the genetic algorithm is used to construct the mathematical model for solving fuzzy vessel scheduling problems based on time optimization, and the minimum delay strategy is used to determine the service sequence. Then, the parameters setting are discussed in detail to find the optimal settings. Finally, an experimental comparative analysis of the randomly generated cases was conducted based on the simulated data. The results show that the designed fuzzy vessel scheduling algorithm reduces the dependence on the port environment, is versatile, and can effectively improve the efficiency of ship schedules and traffic safety compared to other methods. Moreover, it can avoid the problem of the illegal solution occurring in the manual scheduling method.
Ningbo Zhoushan port handled 1.08 billion tons cargoes in 2018 which is considered as the one of biggest ports in the world. There are more than 1 000 ships enter or depart the port per day. Therefore, it is of importance to assess the collision risk for ships passing through the harbor area. In this paper, a novel approach is initially proposed to assess ship collision risk in the harbor area based on collision detection technology of ship domain using automatic identified system (AIS) data. This study aims to build a unified framework of collision risk assessment which does not need to build different models in accordance with the ship domain we selected. To clean the historical motion data of ships, a method for anomaly detection of ship static information based on autoencoder (AE) is proposed. Based on the above proposed method, the ship collision frequency can be estimated, besides, the risk area can also be determined. The results obtained from the method could provide a reference on furthering enhance the navigational safety for the Maritime and Port Authority.
The port waterway network plays an important role in the organization and management of port ship traffic. Due to limited ship operations, conflicts, congestion, and safety issues often arise in port waters. Conflicts between ships can be predicted by collision detection between ships. A novel collision detection algorithm for trajectory pairs is proposed by introducing variable time interval variables. In addition, to improve the overall accuracy of trajectory compression and reduce redundant calculation in collision detection, a multi-factor Douglas-Peucker algorithm adapted to ship trajectory compression is proposed with the consideration of speed and turn constraints. The maximum speed difference of the algorithm is increased by 1.5–2.5%, and the average speed difference increased by 2.0–4.5%. Based on the method mentioned above, the risk assessment framework of maritime collision is established and the risk situation of the waters near Ningbo Zhoushan Port is evaluated and analyzed by using ship historical track data.
It is important to accurately calculate flattening points when reconstructing ship hull models, which require fast and high-precision computation. However, some search algorithms, such as the bisection method, iterate near the optimal value too many times before converging in high-precision computation. The paper proposes a fast high-precision bisection feedback search (FHP-BFS) algorithm to solve the problem. In the FHP-BFS algorithm, the Newton–Raphson (NR) method is adopted to accelerate the convergence speed by considering the iteration characteristics of subintervals. Furthermore, a new feedback mechanism is proposed to control the feedback directions. In addition, an acceleration algorithm, called the interval reformation method, is used to guide the FHP-BFS algorithm for fast convergence. Finally, the flattening algorithm is improved by the FHP-BFS algorithm. In the comparative experiments, the practical efficacy of the FHP-BFS algorithm is first demonstrated, and then the optimal range of the threshold precision is determined. Next the FHP-BFS algorithm is compared to the best existing algorithms. Finally, the performance of the improved flattening algorithm is verified. The experiments demonstrate that the FHP-BFS algorithm has optimal performance among the compared algorithms, and it has an improved computation efficiency while maintaining robustness. The improved flattening algorithm reduces the computation time, ensures smoothness and meets practical engineering requirements.
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