It has been proven that exploring how to achieve an efficient transportation system is a crucial component of every sustainable transportation study. Rail-water intermodal transportation is recognized as one of the future transportation methods for being efficient, economical and environmentally friendly. To improve the efficiency, reduce transportation costs and maximize the resource utilization of outbound intermodal container transportation, based on the relationship between the container central station and the port station in the actual problems, the organization of railway container transportation was studied. A multi-objective optimization model was established in order to minimize the total cost in the process of transportation, which means maximizing the resource utilization and ensuring it is environmentally friendly. Additionally, an improved genetic algorithm (GA) was developed to solve the model. The calculation results of the model are obtained by the simulation calculation. The comparison with the conventional fixed axis transportation organization method proves that the model and algorithm can reduce costs by up to 24.57%. The result also shows that the container transport organization should be tried to satisfy the direct loading and discharging condition of “train-ship,” meanwhile reducing the storage time at the high toll central station. In conclusion, the model and algorithm are feasible and effective. Due to the universality of the model, it can be easily used and generalized in or out of China.

This paper presents a multi-objective optimization model to integrate the scheduling of three types of equipment—railway container operation gantry cranes, yard stacking cranes, and internal trucks—in a multimodal container terminal involving mixed operations of four types of container flows in a partial joint storage yard. The four flows include import/export railway containers and import/export highway containers. The model incorporates realistic constraints such as train operation time windows and container precedence relationships. An adaptive large neighborhood search (ALNS) algorithm, coupled with discrete-event simulation (DES), was designed to solve the problem. Computational experiments were conducted to evaluate various multiple objectives and verified the effectiveness of the proposed solution algorithm through different scale data, as well as provided a sensitivity analysis of the quantitative relationship between the three types of equipment in terms of operation efficiency and equipment utilization in the system. Finally, this paper discusses the impact of the partial joint storage yard strategy on the railway operation area and yard operations. To implement the solution to meet the requirements of efficient equipment utilization and seamless container transshipment operations in a multimodal port, it is imperative to have fast and accurate data sharing among the railway, highway, and port systems. We envisioned that 6G communication would enable that.

Rail–truck intermodal terminals are an important type of dry port and play a vital role in inland freight transport. This paper addresses the container loading problem in rail–truck intermodal terminals considering energy consumption under the sustainability concept. We analyze the effect factors of energy efficiency for container loading operations and develop an optimization model to minimize the total handling time and container reshuffling. A genetic algorithm is designed to obtain the optimal container loading sequence. Computational experiments on a specific Chinese rail–truck intermodal terminal were conducted to evaluate the performance of our approach. Results show our approach has a good performance for different sizes, and the total handing time, reshuffling times and energy consumption of the handling task are prominently decreased.

Track allocation optimization in railway stations is one of the most fundamental problems for scheduling trains, especially in multi-direction high-speed railway stations. With the construction of high-speed rail networks, this kind of station has become increasingly common. However, the track allocation depends not only on the station tracks, train timetable, and rolling stock plan, but also on the resources in the station throat area. As a result, an effective track allocation plan becomes significant but also difficult. In this paper, we consider all these factors to make the results more practicable and an integer linear model that minimizes the total occupation time of resources in the throat area is presented. A flexible track utilization rule is also adopted to this model to fit the characteristics of the multi-direction station. Meanwhile, a detailed explanation of resources’ occupation time is illustrated to facilitate the representation of the conflicting constraints. To resolve these issues, we use a commercial solver with its default parameters. A computational experiment of a station is conducted to verify the effectiveness of the proposed model. The resources utilization plan indicates that the capacity of a station is limited by the throat area, rather than by the station tracks.

As the core operational issue in container terminals, yard crane scheduling problem directly affects the overall operation efficiency of port connecting highway or railway transportation and sea transportation. In practice, the scheduling of yard cranes is subject to many uncertain factors, so the scheme may be inapplicable and needs to be adjusted. From the perspective of proactive strategy, considering fluctuations in arrival time of external trucks as well as varied handling volume of yard cranes, a stochastic programming model is established in this paper to obtain a fixed scheme with the minimum expected value of yard crane makespan and total task waiting time over all the scenarios. The scheme does not require rescheduling when facing different situations. Subsequently, two algorithms based on certain rules are proposed to obtain the yard crane operation scheme in the deterministic environment, which are taken as the basic solution in the uncertain conditions, and then a tailored genetic algorithm is adopted to find the optimal solution with good adaptability to the uncertain scenarios. Finally, we use small-scale examples to compare the performance of algorithms in the deterministic and uncertain environment and then analyze the relationship between different yard crane configurations and the number of tasks. Large-scale experiments are performed to study the operation efficiency of the storage yard with different handling volumes assigned to each yard crane.

Due to the trade imbalance and poor management, a large number of empty containers are piled up after unpacking in importing regions, while the export-oriented areas are in urgent need of empty containers for replenishment. This paper aims to determine the volume of empty containers transferred from the surplus area to the shortage area and the inventory of each node from the operational level. We subdivide container freight stations into rail stations and road stations and consider using sea, road, and railway as transportation modes to transfer empty containers. A multi-period linear programing model of multimodal empty container repositioning is established aiming at minimizing the cost of empty container repositioning. A real case study of the transportation network in Northeast China is conducted to demonstrate that using multiple modes of transportation can significantly reduce the cost of empty container repositioning compared to using a single mode of transportation.