The uncertainty of the arrival time of trucks has increased the complexity of terminal operations. The truck appointment system (TAS) cannot respond to this problem in time, which can easily cause appointment invalidation and reduce the efficiency of truck operations and terminal operations. This paper comprehensively considers the related constraints of truck re-scheduling costs, gate waiting costs, and idle emission costs. With the goal of minimizing the comprehensive operating costs of truck companies and port companies, a dynamic appointment rescheduling model for external trucks based on mixed integer nonlinear programming is established. This paper designs an adaptive quantum revolving door update mechanism and proposes a double-chain real quantum genetic algorithm. The simulation experiment results show that compared with the traditional scheduling, the truck dynamic appointment rescheduling model can effectively reduce the comprehensive operating costs of the truck company and the port company and alleviate the congestion of the port. The probability that the truck cannot arrive at the port on time, the advance time for the truck to confirm the arrival time, and the length of time that the external truck cannot arrive at the port on time have a significant impact on the cost of the reschedule of the TAS. This paper favorably supports the manager’s operational decision-making.

Yard handling is an important part of port logistics and affects the overall efficiency of the container port. The yard crane scheduling is affected by various external factors. For example, the dynamic cut-off time makes the release time of yard cranes variable, and the yard crane task arrangement will change frequently, resulting in a lot of computational time. To increase the flexibility of container yard handling, a twin yard cranes scheduling model is established considering the no-crossing constraints and the dynamic cut-off time. A joint scheduling of PSO and local re-scheduling strategy (LRPSO) is put forward to deal with the problem faster and more effectively. Small-scale and large-scale experiments are simulated to verify the performance of the proposed method. Results show that the scheduling method is more efficient.

Although the importance of digital transformation in contemporary port development has been widely acknowledged, there is little empirical research on the extent to which it promotes sustainable development by reducing costs and increasing efficiency. This study takes the digital transformation of one of the largest ports in northern China—Tangshan Port—as an example, as the application of digital technologies has greatly improved its operational efficiency. By using cargo throughput and container throughput data from Tangshan Port as the experimental group and from Qinhuangdao Port as the control group, difference-in-differences regression models with monthly data and port fixed effects were adopted to clarify the impact of digital transformation on sustainability for different types of cargo throughput, as well as the differential effects of policy impact on port production efficiency and economic performance in the short and long term, in order to examine the impact of digitalization on port operation performance. Our findings demonstrate that digital transformation has a significant positive impact on both port cargo and container throughput, with the long-term effect surpassing the short-term effect. Additionally, regional economic level positively moderates policy impact. These findings provide critical evidence that ports can balance economic growth and environmental sustainability within sustainable development frameworks.

Rural logistics networks face the dual challenge of improving service reliability while maintaining long-term cost efficiency. Drawing on the resource-based view and transaction cost economics, this study examines how cold chain coverage and intelligent sorting contribute to the operational sustainability of urban–rural logistics and whether joint distribution conditions these relationships. Using monthly panel data from 150 outlets within a Chinese postal network from 2017–2023, we estimate outlet and time fixed-effects models with interaction terms. The results show that greater cold chain coverage and intelligent sorting penetration are associated with higher delivery success rates and lower unit delivery costs. However, joint distribution intensity weakens both the service-quality benefits and the cost-reduction effects of these investments, suggesting that cross-organizational coordination may constrain the conversion of specialized and technological resources into operational performance. Further heterogeneity analyses reveal that these performance improvements are concentrated in agricultural counties and geographically concentrated service areas, highlighting the importance of local demand characteristics and network conditions in determining the returns to logistics investment. The findings highlight the importance of aligning infrastructure investment, digital upgrading, and inter-organizational governance with local demand and network conditions.