The upper reaches of the Yangtze River are characterized by a complex channel shape, numerous curved shoals, and significant variations in water level. The conditions for constructing the waterway are complex and changeable. In recent years, the Chinese government has increased investment in waterway construction in this area. However, the new cross-river bridges often face problems such as limited site selection, limited span and scale, a high risk of ship collision, and deteriorating navigation conditions. These issues have an irreversible impact on navigation development. Therefore, it is urgent to develop a technology to guarantee bridge navigation safety that is suitable for the complex waterway in the upper reaches of the Yangtze River. Based on the navigation conditions of complex bridges in the upper reaches of the Yangtze River, this paper proposes a safety evaluation system for full-cycle bridge navigation, analyzed in five stages: planning, design, construction, operation and demolition. This paper also proposes a key technical system for full-cycle bridge navigation safety, adapted to complex waterway bridges in mountainous areas in the upper reaches of the Yangtze River. This technology can provide guidance for navigating bridges over complex waterways in the upper reaches of the Yangtze River and is of practical significance.

To solve the problems of complex decision-making and the difficulty of global optimisation involving many factors, this paper establishes a scheduling model for maritime search and rescue forces and uses a second-generation non-dominant genetic algorithm based on a reduplication strategy (DW-NSGA-Ⅱ) to solve these problems. Firstly, the probability of a successful search and survival (POSAS) is elaborated upon, taking into account the survival probability of the target and the relevant mathematical model of the time it takes the search and rescue force to arrive at the search area. A search and rescue force dispatch model is then established with the following optimisation goals: the maximum search success rate, the shortest arrival time of search and rescue materials, and the minimum search and rescue cost. Secondly, to solve the problems of crowding, distance failure, and poor global optimisation caused by multiple repeated solutions when solving the search and rescue force scheduling model using the second-generation non-dominant genetic algorithm (NSGA-Ⅱ), a second-generation non-dominant genetic algorithm based on a reduplication strategy (DW-NSGA-Ⅱ) is proposed. Finally, an accident is used as an example to demonstrate the use of DW-NSGA-Ⅱ and NSGA-Ⅱ to solve the model, with the resulting optimisation outcomes being compared. The experimental results show that the proposed method can consider marine environmental information, accident rescue requirements and search and rescue forces to formulate a reasonable and effective search and rescue force scheduling scheme. The DW-NSGA-Ⅱ algorithm's optimisation effect is better than that of the NSGA-Ⅱ algorithm under the same initial conditions, which verifies the superiority of DW-NSGA-Ⅱ in search and rescue force dispatch.

Ocean waves are characterised as random and non-linear. Predicting significant wave height is critical for ensuring the safety of ship navigation and route planning. In the present study, the Grey Wolf optimiser was improved by optimising the search mechanism and coupled it with the Grouping Method Data Handling model to construct an effective significant wave height prediction model. This novel prediction model was validated using a significant wave height dataset. The weights of the different model variables were also explored. The results show that the IGWO-GMDH model is more accurate. The mean square error decreased by 2.65%, and the root mean square error decreased by approximately 1.35%. The standard deviation was reduced by 2.14%. Additionally, the weights of the wave characteristic parameters and the wind field data are relatively high; combining these would significantly impact the model's accuracy. The IGWO-GMDH model will provide more robust predictions of significant wave height and support research into ship navigation safety and route planning and optimisation.

In order to solve the problem of difficult control of rebound and large impact during the berthing process of vessels not under command, a variable throttling active buffer method is proposed. The principle of the variable throttling active buffer for vessels not under command has been designed. A mathematical model of the system is established. A simulation model of the system is built based on AMESim. The simulation results of the passive buffer system and the active variable throttle system are then compared. The effectiveness of the variable throttle active buffer system is verified. The main analysis focuses on the pressure in the variable throttle chamber, the displacement of the ship berthing buffer and the speed. The influence of the opening pressure of the variable throttle valve and the overflow valve on the performance of the active variable throttle buffer is studied. The results show that, when using the berthing variable throttle active buffer system, the vessel decelerates smoothly without rebound during the berthing process and there is no pressure impact or fluctuation in the variable throttle chamber. Increasing the variable throttle opening prolongs the pressure response time of the variable throttle chamber. Increasing the relief valve opening pressure prolongs the pressure attenuation time of the variable throttle chamber. Under low-normal speed or light load berthing conditions, the ship berthing buffer decelerates gently.

Qinzhou Port, one of the largest in the Beibu Gulf, had a throughput of over 170 million tonnes and a container throughput of more than 5.4 million TEUs in 2022. The port is currently considering adopting the "seamless-connection mode" scheduling strategy to improve the operational efficiency of container ships. However, quantitative analysis tools are lacking. Using AnyLogic simulation software, this study has created a simulation model of the entire process of arriving at the port, waiting at the anchorage, entering the channel, anchoring, and leaving the port, both under the 'seamless-connection mode' and the existing scheduling modes for container ships at Qinzhou Port. The simulation results show that, compared with the existing scheduling mode, the average waiting time for container ships is reduced by 50.7%, while the threshold value for harbour service ships can be increased by 19.5%. These results provide port authorities with the necessary theoretical and data-driven support to formulate relevant policies and traffic rules.

The International Association of Classification Societies has updated the North Atlantic wave scatter diagram and supplementary requirements. A series of ships, including bulk carriers, oil tankers, container ships, ore carriers, LNG carriers, PCTC ships and passenger ships, were used to analyse the influence of the updated wave scatter diagram on a ship's wave load through long-term wave load prediction. The results of the analysis show that, compared with the original North Atlantic wave scatter diagram, the new diagram and supplementary requirements have a different impact on different ship types, typically decreasing by 0~40%. The results of this study provide a reference for determining the extreme wave load of ships above the new scatter diagram.

Optimising pilot scheduling can reduce working hours and labour costs for pilots, while offering new approaches to pilot training. This paper addresses the scheduling of pilots for inbound and outbound vessels in a one-way waterway by establishing a joint optimisation model, with the aim of minimising total vessel waiting time, total pilot working hours and labour costs. It proposes a two-stage heuristic algorithm that combines an imperialist competitive algorithm, an adaptive evolutionary strategy, and a variable neighbourhood search (VNS) algorithm. Case studies and comparative experiments demonstrate the effectiveness of the model and algorithm. Compared with the traditional first-come, first-served (FCFS) rule, the proposed approach reduces pilots' average working hours and labour costs by 17.4% and 12.4%, respectively. Therefore, integrating the model and algorithm into pilot training programmes or operational guidelines could enhance coordination among port departments, improve organisational efficiency and service quality, and support the development of green and smart ports.

Inland river navigation plays an important role in supporting the domestic and international dual circulation by connecting international and domestic markets. However, the navigable channels of inland waterways are limited. With the increased demand for inland vessel traffic and higher requirements for vessel traffic services, attention is increasingly being paid to the safety and efficiency of inland vessel traffic. It is necessary to rigorously explore the regularity and characteristics of inland vessel traffic flow and conduct research into traffic efficiency, safety and available channel capacity. Traffic flow simulation is one of the key methods employed in this type of research. By investigating and analysing the navigation behaviour characteristics of inland vessels, a cellular automata-based model of vessel traffic flow in inland waterways is established, and a simulation experiment is carried out based on a straight segment of the Yangtze River. The simulation results demonstrate that the model can accurately predict vessel behaviour, such as overtaking, entering and leaving waterways. The simulated traffic flow characteristics in trajectory simulations and spatial-temporal diagrams align closely with the actual situation. These results can provide theoretical and technical support for analysing inland waterway traffic flow, supervising vessel traffic, planning waterways, and forecasting traffic flow.

This paper studied the problem of distributing commodities for RoRo ships. Taking into account the initial inventory level at each demand port, the paper proposes a flexible calling strategy for RoRo ships transporting commodity vehicles within multiple voyage planning periods. A collaborative optimization model for routing and stowage was established for RoRo ships, and an improved genetic algorithm was designed to solve it. The results of the numerical example demonstrate that this flexible calling strategy can reduce the total distribution cost of RoRo ships by 1.9%. There is a difference of about 4% in fuel consumption between large and small RoRo ships for round-trip voyages on the same route. Shipping companies can also reduce total costs by arranging different types of RoRo ship for distribution. When the safety stock is set to a moderate level, the total cost during the planning period is minimized. These research conclusions can provide a useful reference for shipping companies when making decisions about the distribution of commodities with RoRo ships.

To improve the effectiveness of Unmanned Surface Vehicle (USV) path planning in complex marine environments, and to address the issue of low operational efficiency in dynamic environments, a new Dynamic Window Approach (DWA) for USV path planning has been developed. Firstly, the target water area range is determined based on the USV's initial and target positions, and the water area is modelled using a grid system. Secondly, the forces exerted on the USV by wind, waves and currents are calculated and combined with the USV's mass to produce an acceleration value, thereby forming a kinematic model of the USV under the influence of the marine environment. Thirdly, the maximum values of linear and angular acceleration of the USV are determined using the Fossen ship dynamics model, thus obtaining the actual reachable speed set of the USV. Finally, an adaptive weight adjustment algorithm is used to improve DWA and plan the USV path, considering the heading, safe distance and speed factors. Simulation experiments were conducted in the waters near the Zhoushan Islands using the USV "Zhi Kun" to verify the reliability of the model. The results show that, compared with the comparative algorithm, the proposed algorithm performs better in terms of running time, simulation step size, change in bow direction amplitude, change in speed amplitude, and length of the planned path. The improved DWA-planned path ensures the USV can reach its destination safely and quickly, providing a reference for improving the autonomous navigation performance and efficient utilisation of USVs.