With the increasing maturity of automatic driving technology, the commercial value of driverless container trucks has been gradually excavated. Compared with social roads, the internal roads in the port area have certain practicing advantages. By taking into account the operational characteristics of the driverless electric container truck and the coordination of quay and yard cranes, this paper aims to explore the configuration and optimized scheduling model of the driverless electric container truck with the objective of minimizing overall energy consumption. The results show that the optimized allocation and scheduling of driverless electric trucks can minimize the total energy consumption of terminal operation without delaying the shipping schedule, and has obvious advantages over traditional manual driving diesel trucks and Automated Guided Vehicles in terms of operation efficiency, economy, and sociality. The results can also provide certain decision-making reference for the selection of horizontal transportation equipment and collaborative scheduling of multi-type loading and unloading equipment resources of container terminal operators.

Shore power represents one of the principal solutions for the green transformation within the port industry. It significantly aids in the reduction in carbon emissions from vessels while they are berthed in port, yet often necessitates an effective promotional strategy to foster its installation and utilization. Stakeholders including port authorities, ship operators, and local governments all play a crucial role in achieving this objective. This paper employs a tripartite evolutionary game model in conjunction with a system dynamics model to investigate the evolutionary responses of stakeholders when policy tools are applied, and consequently, to elucidate the dynamics of strategy effectiveness. In this context, six business scenarios are developed to ascertain the potential impacts of implementing subsidies and carbon taxes. The findings demonstrate that any singular strategy, whether a subsidy or a carbon tax, is inadequate for the successful advancement of shore power; on the contrary, a government-led, integrated, and dynamic reward–punishment strategy aids in stabilizing the inherent fluctuations within this game process. Moreover, the initial willingness of ship operators exerts a considerably greater influence than that of the other two stakeholders.

The idea of this paper comes from the need for a practical layout design for the subsea pipe line network and the power transmission network of offshore wind farms with subsea cables, which are both subsea transmission networks with line-shaped conduction structures. In this paper, this practical need is treated as an location-allocation problem, with the objective of minimizing the total cost, and a mixed-integer linear programming model (MILP) for layout optimization is developed. Through the model, the locations of service centers and theit corresponding sizes, the allocations between customers and service centers, as well as the transmission routes can all be figured out. This work makes two key contributions. First, facilities’ capacity restrictions and the avoidance of subsea obstacles are both integrated, making the description of the layout closer to practical situations. Secondly, a “global to local” search process based on the Delaunay triangulation method is constructed to solve the model, resulting in a high-quality solution. An offshore field layout design scenario is taken as a case study, through which the validity, feasibility, and stability of the proposed model, as well as the solution strategy, are presented. Furthermore, in the case study, the effect of the manifold number on the layout optimization is analyzed, indicating the flexibility of the model’s applications.

The increasing of deepwater oil field developments brings a growing need for thermal management to prevent hydrate and wax formations in the subsea production system, due to the low environment temperature and long distance transportation. Pipeline insulation coating is a typical strategy for thermal management. In a subsea production system, pressure, temperature, flow rate and length of each flowline vary, leading to a different thermal performance of the fluid inside. Therefore, the insulation coating should be carefully designed from the overall perspective to minimize the total material volume, thus reducing the cost. In this paper, an optimization model for the insulation material volume of a wellhead-manifold-FPSO production system is proposed. Then, the best insulation thickness of each sub-sea flowline can be determined under given flow parameters and temperature requirements. The factor that defines the temperature drop from riser base to the top termination is introduced and analyzed. There is a proper temperature drop factor associated with the insulation material volume for subsea flowlines, as well as a proper insulation capacity for the risers. This optimization model can define the subsea system insulation and provide reliable results for cost estimation.