The implementation of China’s Belt and Road Initiative macro strategy has promoted exchanges and cooperation between China and Europe and countries along the route. The operation of the China Railway Express provides a new transportation platform for China–Europe trade. The sustainable development of the China Railway Express has a great significance in terms of promoting the growth of China–Europe trade and meeting the demand for freight in Asia and Europe. Its time-saving advantage over shipping and its economic advantage over air transport cannot be ignored. This paper is based on the discrete selection model of stochastic utility theory. The paper constructs a multi-logit model based on generalized cost functions, including economics, timeliness, reliability, convenience, safety, and environmental protection. To calculate the market share of the China Railway Express and China–Europe Shipping, the paper conducts a quantitative analysis of the market competitiveness of the China Railway Express. Then, the sensitivity analysis and elastic analysis are carried out on the China Railway Express freight rate, the Chinese road freight rate, the China Railway Express service fee, the China Railway Express travelling speed, the China Railway Express sending operation time at the departure station, the China Railway Express transportation time error, the China Railway Express transportation frequency, and the China Railway Express carbon emissions per unit. Finally, based on the analysis results, suggestions for promoting the sustainable development of the China Railway Express are given.

The height and stagger of the contact wire directly affect the energy supply of high-speed trains. To ensure the operation safety, there is an urgent demand for high-speed railways to measure the static parameters of contact wires all over the line with high precision and efficiency. However, this issue is barely discussed. Concerning the issue, this paper proposes a UAV-LiDAR-based measuring framework for the static height and stagger of high-speed railway contact wire. By mounting LiDAR on the UAV, the framework can efficiently collect data from the lines in service without occupying the train operating-diagrams. It is extremely significant for the high-speed and high-density railways. Then, we present self-adaptive extraction algorithms to extract critical infrastructures (rails, contact wires, masts and other suspensions) based on their specific geometric characteristics as well as the continuity and consistency of the spatial distributions along the line. Finally, the height and stagger are calculated by formulas automatically. To verify the framework in practice, we tested it on Beijing-Shanghai high-speed railway, which is the busiest high-speed railway in China. It is shown that the measurement error is within 9mm and the framework has potential to reform the inspection of high-speed railways.

The sustained and steady development of China’s economy has led to the rapid improvement of the logistics. At the same time, the rise of the e-commerce mode has given rise to a huge demand for express delivery and the express industry has entered a period of boom. Fortunately, China’s high-speed rail network has been networked, and the development of a high-speed rail express train has entered the test stage. After the high-speed rail express train is put into use, it could effectively relieve the pressure of highway transportation and significantly reduce transport pollution. To make better use of high-speed rail transport resources and give full play to its green and efficient advantages, this study established a two-stage model of a high-speed rail express train operation plan. In the first stage, a train candidate set generation model aiming for the minimum total cost of train operation was established that considered the high-speed line carrying capacity, section flow capacity, and OD requirement satisfaction constraints, which reduces the scale of train spare parts and improves the efficiency of solution. In addition, a column generation algorithm was designed to solve the model. In the second stage, an accurate flow distribution model aiming for the optimal economic efficiency was established, and then the high-speed express train operation plan was designed completely. The computational results are encouraging and demonstrate the effectiveness of the model and solution method.

Sustainable development of transport systems is a common topic of concern and effort in multiple countries, in which reducing carbon emissions is one of the core goals. Multimodal transport is an effective way to achieve carbon emission reduction and to efficiently utilize transport resources. The intercontinental transport system, represented by the Euro–China Expressway, is a prominent exploration that has recently received attention, which promotes the sustainable development of transport between countries and carbon emission reduction. In the intercontinental multimodal transport system, the reasonable connection of roads and railways, especially the optimization of consolidation, is an important link which affects the system’s carbon emissions. This paper focuses on the consolidation of sustainable multimodal transport and summarizes the multimodal transport two-echelon location-routing problem with consolidation (MT-2E-LRP-C). We aim to solve multimodal consolidation optimization problem, especially locations of multimodal station, by routing of highway and railway. We propose a two-layer mixed integer linear problem (MILP) model, which highlights the consolidation of roads and railways, focuses on road and rail transport connections, and optimizes road routes and railway schemes. To validate the MT-2E-LRP-C model, we design a series of random instances for different quantities of nodes. In order to solve large-scale instances and realistic transport problems, we propose a hybrid differential evolution algorithm, which decomposes the problem into a railway layer and a highway layer for heuristic algorithm solving. Furthermore, the MILP model and algorithm are tested by small-scale random instances, and the hybrid differential evolution algorithm is solved for the large-scale random instances. Finally, we solve the realist instance from the Euro–China Expressway to develop instructive conclusions.

This paper studies the line planning optimization problem based on the coordinate mode of high-speed railway (HSR) passenger trains and freight trains. The multi objective nonlinear mixed integer programming model of HSR passenger train and freight train line planning with passengers and freight is designed on the basis of comprehensive consideration of passenger and freight transport demand. Then, in order to simultaneously determine the types, origin and destination stations, operation sections, stop schemes, operation frequencies, and demand allocation of HSR passenger trains and freight trains, the model is solved iteratively using a hybrid heuristic algorithm combining a column generation algorithm and a genetic algorithm. Finally, a numerical experiment based on the operation data of China’s Dalian-Harbin HSR line is implemented to verify the effectiveness of the proposed model and algorithm, and the solution performance of the CPLEX solver and the hybrid heuristic algorithm is compared. The results show that both the CPLEX solver and the hybrid heuristic algorithm can obtain the global optimal solution set. With the expansion of the scale of the problem, the solution quality and convergence efficiency of the hybrid heuristic algorithm have significantly improved, and it can solve large-scale problems and obtain satisfactory solutions within a shorter time.