Zhejiang Province, as a vital hub in China's "Belt and Road" strategy, holds significant research significance in terms of port efficiency. Ports, as crucial nodes in the trade and transportation system, play a pivotal role in evaluating port development through their operational efficiency. This study examines the impact of environmental factors, including inland economic level and regional industrial structure, on port efficiency and analyzes the spatiotemporal evolution of port efficiency using a three-stage DEA approach. The results indicate that the average port efficiency in Zhejiang Province from 2011 to 2020 is relatively low, exhibiting a certain degree of fluctuation over time with a stable upward trend. After removing the environmental factors, there is a substantial decrease in overall scale efficiency while pure technical efficiency shows a significant improvement, suggesting estimation bias in port efficiency due to environmental factors. Moreover, coastal ports demonstrate noticeably higher efficiency compared to inland ports in terms of spatial distribution. Finally, targeted strategies and recommendations are proposed to enhance the comprehensive competitiveness of Zhejiang Province's ports within the framework of China's "Belt and Road" strategy.

Due to the uncertain interference of the external and internal environment of the system, the vulnerability of emergency logistics system (ELS) has become increasingly prominent. Based on the VSD (Vulnerability-Scoping-Diagram) model, this study provides a vulnerability assessment index of ELS with 16 indicators in 3 dimensions (exposure, sensitivity and adaptability). Then, a system dynamic model (SDM) is constructed to simulate and assess the ELS vulnerability and an empirical study is carried out by using the data of Shaanxi Province. The findings show that the ELS vulnerability is on the decline in Shaanxi from 2012 to 2020. Specifically, the adaptability is rising annually, the sensitivity shows a downward trend with a small fluctuation, and the curve of exposure is consistent with vulnerability and has a declining trend direction. The results give beneficial enlightenment for governors and other social organizations. This study provides a new way to explore and resolve the vulnerability issue of ELS.

Strengthening regional multi-level rail transit connectivity can promote the sound development of the comprehensive transportation system of urban ag-glomerations. And it can promote the faster integration of regional cities and the improvement of overall competitiveness. This paper studies the problem of "how to choose the appropriate network operation organization mode". The evaluation index system is established, and the concept of accessibility is innovatively introduced. From the four aspects of urban development co-ordination, passenger service level, rail company operation effect and project implementation, the operation organization mode is determined by quantitative comparison. Finally, the research results are applied to the selection of operation organization mode of urban railway and urban rail transit in a city, which proves that the method has good applicability.

Reducing fuel consumption is an important part of improving the efficiency and quality of civil aviation operations and realizing the national strategy of ‘peak carbon dioxide emissions’. The industry and academia still use the BADA (Base of Aircraft Data) data model as the benchmark for the calculation of fuel consumption , but this method has the shortcoming of many influencing factors and large errors in the calculation results. This paper proposed a new method for calculating fuel consumption based on QAR (Quick Access Recorder) and ACARS (Aircraft Communications Addressing and Reporting System) data. For QAR data, the fuel consumption is calculated based on the flight altitude and fuel flow indicators which was used to identify each stage of the flight. For ACARS data, fuel consumption is calculated based on several key action time points and remaining fuel flow. The accuracy of the two algorithms is higher than 95%, and the QAR method is more accurate, but ACARS method is more practical.

With the development of computer and artificial intelligence technology, the transportation and production logistics industry is gradually realizing the deep integration of intelligence, informationization, and industrialization. This paper takes the assembly jobshop problem with high complexity as an example, using the output feature data of simulation models to explore the correlation between the product completion time in the assembly jobshop and its influencing factors, and propose a more accurate prediction method for the product completion time in the assembly jobshop. Firstly, using Plant Simulation software to build a complete dynamic assembly jobshop simulation model. Then, according to the production data obtained from the simulation model, conduct feature variable analysis, and statistically identify significant feature variables as inputs for the prediction model. Secondly, adopt machine learning algorithms such as support vector machines, decision trees, and random forests to train and compare prediction models based on significant feature data. To further improve prediction accuracy, combine seagull optimization algorithm to improve the random forest prediction model, and design the SOA-RF prediction model. The experimental results show that the three evaluation indicators (R2, RMSE, MSE) of SOA-RF were 0.9041, 10.17, and 103.44 on the test set, respectively. Compared with the comparative algorithm, it achieved better performance and could provide precise data support for production logistics activities.

In this paper, on the basis of elaborating the mechanism of the mutual coordination development of urban road freight and regional economy, the index system of coupling coordination degree between road freight and regional economy is established, and the mathematical model of coupling coordination degree is introduced to empirically analyze the coupling coordination status of road freight and regional economy in three areas of Beijing-Tianjin-Hebei city cluster. The results show that from 2013 to 2020, the overall level of comprehensive development of urban freight transport and regional economy in Beijing, Tianjin and Hebei is in a trend of steady improvement, but the development of urban freight transport in Hebei Province is significantly better than that in Beijing and Tianjin, and the development of regional economy in Beijing is better than that in Hebei and Tianjin; in recent years, the coupled and coordinated development of road freight transport and regional economy in all three places is transformed into a good situation, and Hebei Province always keeps the three In recent years, the coupled and coordinated development of road freight and regional economy in all three regions has turned out to be good, and Hebei Province has always maintained the best status among the three. Based on the research results, corresponding conclusions and suggestions are proposed.

Container shipping has been regarded as the backbone of the global maritime logistics system. There usually exist severe cancellations of container slots bookings by the customers (i.e., consignors) in the container shipping market, which significantly affect the capacity utilization and the profitability of a shipping company. Inspired by the practice of the global shipping companies (such as Maersk), this paper proposes the concept of the target show-up rate and dead freight to control the customer's cancellation behaviour. The target show-up rate indicates the show-up rate of the booked slots that should be satisfied by the customers; otherwise, the dead freight will be charged by the shipping company for the unfulfillment of booked container slots. This paper first extends the Newsvendor model to attain the relationship among optimal booking number, target show-up rate and unit dead freight. Based on this relationship, an optimization model is formulated to optimize the target rate and dead freight to maximize profit of the shipping company. The optimal conditions of these two terms are also obtained. Finally, a case study shows that considering the target show-up rate and dead freight can significantly improve the profit of the shipping companies.

Currently, the major modes of transportation for the import and export of commercial cars are Ro-Ro because of its high volume and low cost. In order to address the lack of a scientific quota development approach for commercial vehicle Ro-Ro terminals, we present a TOPSIS-based quota development method in this study. The technique thoroughly evaluates the role of workers in Ro-Ro loading and unloading operations and takes into account the influence of three indicators on labor quota determination, namely the psychological quality, physical quality, and technical level of workers. By integrating the definition of the average advanced level with the weight coefficients of each index, the TOPSIS approach was utilized to thoroughly evaluate the employees and establish the labor quota level. The data collected at A Ro-Ro terminal also serves to validate the process. The findings demonstrate that the strategy suggested in this research can create a quota level that corresponds to the enterprise's actual production condition and can also serve as a guide for establishing and managing labor quotas in commercial Ro-Ro terminals.

In order to further improve the traffic safety service and emergency control of highway under adverse weather, and to solve the problems of high traffic accidents rate and low traffic efficiency of highway under the weather of traffic hazard - fog, this paper proposed a traffic risk-oriented classification and control strategy for emergency situations. By analyzing the psychological and behavioral characteristics of drivers in foggy weather, it is proposed that the decreases in driver's visual recognition distance is the main causation of traffic disasters risk in foggy weather. Based on the impact degree of drivers' visual recognition distance decrease on operating speed, the weather of traffic hazard - fog in highway is divided into three risk levels: high, medium and low. Then by using the relationship model between visibility in foggy weather and driver's visual recognition distance, the study proposes the corresponding index thresholds of the early warning management and speed limit management for different risk levels of highway, and specifies the setting principles and length of the early warning section, finally forms a set of refined traffic emergency classification and control scheme for highway foggy segment.

The urban rail transit carries a large amount of passenger flow and has high operational reliability and safety requirements. Risk assessment of urban rail transit can improve the comprehensiveness and pertinence of operation and maintenance. In response to the problems of inconsistent comparison matrices and long decision-making time in traditional analytic hierarchy process, a risk assessment method for urban rail transit was designed by introducing fuzzy consistent matrices, combining fuzzy comprehensive evaluation method and analytic hierarchy process. A risk assessment index system and risk assessment model for urban rail transit were constructed. Based on actual operational data, experts conducted risk assessments on the urban rail transit in Chengdu and Hangzhou, and determined the risk factors that have a significant impact on the operational safety of the urban rail transit. Compared with the traditional analytic hierarchy process, the analysis results show that this method can effectively assess the risk of urban rail transit, provide reference for the operation and maintenance of urban rail transit, and has the advantages of consistent comparison matrices and high decision-making efficiency.