Search Results (12)

The spatial separation of port yards and railway hubs, which relies on external truck drayage as a necessary link, hampers the seamless transshipment of sea–rail intermodal containers between ports and railway hubs. This creates challenges in synchronizing yard cranes (YCs) at the port terminal, external trucks (ETs) on the road, and rail-mounted gantry cranes (RMGs) at the railway hub. However, most existing studies focus on equipment scheduling or container transshipment organization under the port–railway integration mode, often overlooking critical time window constraints, such as train schedules and export container delivery deadlines. Therefore, this study investigates the collaborative scheduling of YCs, ETs, and RMGs for synchronized loading and unloading under the port–railway separation mode. A mixed-integer programming (MIP) model is developed to minimize the maximum makespan of all tasks and the empty-load time of ETs, considering practical time window constraints. Given the NP-hard complexity of this problem, an improved genetic algorithm (GA) integrated with a “First Accessible Machinery” rule is designed. Extensive numerical experiments are conducted to validate the correctness of the proposed model and the performance of the solution algorithm. The improved GA demonstrates a 6.08% better solution quality and a 97.94% reduction in computation time compared to Gurobi for small-scale instances. For medium to large-scale instances, it outperforms the adaptive large neighborhood search (ALNS) algorithm by 1.51% in solution quality and reduces computation time by 45.71%. Furthermore, the impacts of objective weights, equipment configuration schemes, port–railway distance, and time window width are analyzed to provide valuable managerial insights for decision-making to improve the overall efficiency of sea–rail intermodal systems. Full article

In order to integrate the use of transportation resources, develop a reasonable sea–rail intermodal container transportation plan, and achieve cost reduction and efficiency improvement of the multimodal transportation system, a method for predicting the daily freight volume of sea–rail intermodal transportation based on a convolutional neural network (CNN) algorithm is proposed and a new feature processing method is used: weight assignment (WA). Firstly, we use qualitative methods to preliminarily select the indicators, and then use multiple interpolation to fill in the missing raw data. Next, Pearson and Spearman quantitative analysis methods are used, and the analysis results are grouped using the k-means, with the high correlation groups assigned high weights. Next, we use quadratic interpolation to obtain the daily data. Finally, a weight assignment-enhanced convolutional neural network (WACNN) model and seven other mainstream models are constructed, using the Yingkou port container throughput prediction as a case study. The research results indicate that the WACNN prediction model has the best performance and strong robustness. The research results can provide a reference basis for the planning of sea–rail intermodal container transportation and the allocation of transportation resources, and achieve the overall efficiency improvement of logistics systems. Full article

The sea–rail intermodal container terminal serves as a key transportation hub for green logistics, where efficient resource coordination directly enhances multimodal connectivity and operational synergy. To address limited storage capacity and trans-shipment inefficiencies, this study innovatively proposes a resource-sharing strategy between the seaport and the railway container terminal, focusing on the joint allocation of yard space and internal trucks. For indirect trans-shipment operations between ships, the port, the railway container terminal, and trains, a mixed-integer programming model is formulated with the objective of minimizing the container trans-shipment cost and the weighted turnaround time of ships and trains. This model simultaneously determines yard allocation, container transfers, and truck allocation. A two-layer hybrid heuristic algorithm incorporating adaptive Particle Swarm Optimization and Greedy Rules is designed. Numerical experiments verify the model and algorithm performance, revealing that the proposed method achieves an optimality gap of only 1.82% compared to CPLEX in small-scale instances while outperforming benchmark algorithms in solution quality. And the shared yard strategy enhances ship and train turnaround efficiency by an average of 33.45% over traditional storage form. Sensitivity analysis considering multiple realistic factors further confirms the robustness and generalizability. This study provides a theoretical foundation for sustainable port–railway collaboration development. Full article

The U-shaped automated container terminal (U-ACT) meets the requirements of sea-rail intermodal transportation with its unique layout. However, this layout also presents challenges, such as complex container transshipment planning and challenging equipment scheduling, which limit further improvements in overall efficiency. This paper focuses on the integrated scheduling of horizontal transportation and container-handling equipment for container transshipment at U-ACT. To minimize operation time and energy consumption while addressing path conflicts among container trucks, we designed a two-layer scheduling model to generate an optimal scheduling scheme for each automated device. Given the complexity of the problem, we developed a reinforcement learning-driven hyper-heuristic algorithm (RLHA) capable of efficiently searching for near-optimal solutions. Small-scale experiments demonstrate that our RLHA outperforms other algorithms, improving optimization results by 5.14% to 28.87% when the number of container operation tasks reaches 100. Finally, large-scale experiments were conducted to analyze key factors impacting sea-rail intermodal transport operations at U-ACT, providing a foundation for practical optimization. Full article

Port-centric intermodal transshipment hubs are significant nodes in the global freight network and are likewise the gateway to a country’s external communications. It is vital to increase the service capacity of PCITHs, and it is necessary to assess the service capacity of port-centric intermodal transshipment hubs to respond to the growth of economies and global freight needs. This study provides a detailed definition of port-centric intermodal transshipment hubs through a review of relevant kinds of works from the literature and analyzes their primary functions. Based on the research perspective of sea–rail intermodal transportation, the three evaluation dimensions of service capacity of port-centric intermodal transshipment hubs are divided into radiation scale capacity, transportation connection capacity, and resource integration capacity, focusing on the functions of cargo aggregation, cargo transfer, and connection of different transportation modes. The service capacity evaluation indicators were then selected based on the three dimensions. The subjective and objective weightings were calculated by the G1 weighting method and the modified CRITIC method, and the combination weightings were determined based on game theory. The service capability of port-centric intermodal transshipment hubs was evaluated by the fuzzy matter element method, and the evaluation results were quantified by the Euclidean closeness degree. Finally, through the barrier degree model, the current indicators of PCITHs that urgently need improvement were explored, and targeted improvement suggestions are proposed in this paper. The results show that Tianjin Port has the highest service capacity, followed by Ningbo Zhoushan Port. The port rail dedicated line mileage is the most critical area that needs attention in Ningbo Zhoushan Port and Qingdao Port. Tianjin Port needs to improve the container sea–rail transportation volume, while Guangzhou Port and Xiamen Port need to improve the sea–rail container handling capacity. Full article

A new layout of the U-shaped automated terminal is more convenient to connect between the terminal and the railway. In this study, a sort of cluster scheduling method for multiple equipment between a U-shaped automated terminal yard and a railway yard is proposed. The innovation points are as follows: (1) Considering that the rail gantry crane (RGC), intelligent guided vehicle (IGV), and double cantilever rail crane (DCRC) usually work in groups, they are grouped and cluster-scheduled. (2) A hybrid integer programming model is established to minimize container transit times, and non-crossing constraints and safe distance constraints are included to reflect complex interactions among terminal equipment. (3) An ADMM (Alternating Direction Method of Multipliers)-based framework is proposed to dualize the hard-edge constraints and break the cluster scheduling problem down into a specific subproblem set of RGCs, IGVs, and DCRCs, and their time cost is iteratively adjusted to improve the solution quality. The experiment results show that the solution of the proposed method, which can effectively avoid IGV conflict, is better than that of the standard Lagrange relaxation (LR) when the number of equipments participating in scheduling increases. This study on multi-equipment cluster scheduling is conducive to improving the collaborative handling and continuous work of terminal equipment, and improving the efficiency of the automated terminal and the sea–rail intermodal transport. Full article

Global warming trends and the rapid reduction of summer Arctic sea ice extent have increased the feasibility of transarctic transport. How the process of glacier melting affects the existing containerized sea–rail shipping network and container flow assignment has become a challenging economic and policy issue. This paper first examines the meteorological influences on glacier melting and the assignment of container flow over the existing sea–rail network. Then, a three-layer simulation framework is constructed, with the upper layer simulating glacier melting based on the raster grid, the middle layer combining a grid and topology analysis to simulate the evolution of the global sea–rail network and the lower layer establishing a concave cost network flow model to simulate the container flow assignment. Finally, we use MicroCity to achieve the dynamic optimization and simulation of global container flow assignment, solving the large-scale sea–rail shipping network traffic assignment problem. The simulation results show that the proposed model and solution algorithm are feasible and effective, revealing the variation of container flow assignment in the global sea–rail shipping network under different Arctic ice melting scenarios. For instance, in the summer of 2050, the Arctic routes will share the global container flows, resulting in a significant reduction of container flows in the Malacca Strait, Suez Canal and Panama Canal. Full article

With the advantages of large volume, low unit transportation costs, as well as sustainable and stable transport capacity, China in recent years has actively promoted the innovative pilot of double-stack container sea-rail intermodal transport in the Ningbo-Zhoushan port. In this study, a new synchronous handling technology is proposed to improve the handling efficiency of double-stack container trains at sea-rail intermodal terminals. This research primarily focuses on the design of an LDAGV (Automatic Guided Vehicle with Loading and Discharging Function) and a new special articulated flat car for double-stack container trains, while also optimizing the overall layout of the container terminal yard. It then evaluates nine double-stack container stacking forms based on the requirements of transport gauge and center of gravity height. Finally, using data from the Ningbo Beilun No. 3 container terminal, a cost-benefit analysis is performed to compare the traditional handling scheme for common double-stack container trains and the new synchronous handling scheme for double-stack container trains with new special articulated flat car. The results show that the application of new synchronous handling technology has obvious advantages in terms of reducing the handling time and operation cost of double-stack container trains in sea-rail intermodal container terminals, as well as enriching the stacking forms of double-tier containers on the new special articulated flat car, thus reducing the difficulty of collecting cargoes and the organization of container source.
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It is now widely accepted that the locations of intermediate facilities, such as logistics platforms or inland ports, are key elements of multimodal freight distribution networks and heavily influence their effectiveness. This crucial role of localization decisions is even more significant if we consider their impact on the external costs of the entire logistic corridor, with reference to the cost components associated with environmental sustainability. This paper faces a facility location problem concerning a port system network serving inbound container flows arriving by sea and travelling via road and/or rail towards the hinterland. The aim is to evaluate the impact of externalities on the overall management of the distribution network, including location decisions, flow routing and transport mode choice. We present a Mixed Integer Linear Programming (MILP) model having the goal of minimizing both the location and shipping costs, while accounting for external cost components. In particular, as a novel environmental issue, we propose three different objective functions including congestion, air pollution, and, incidentally, noise and infrastructure deterioration. We allow the containerized flows to be split among several capacitated facilities and road and rail transport modalities. The reported computational experimentation refers to different intermodal freight logistic networks through real data derived from the logistic network departing from the maritime terminals associated with the port of the Ligurian region towards their main destinations in the north-west side of Italy. Finally, we evaluate the impact on both flows and total costs due to a closure or a capacity reduction on some links of the network. The evidence of the impact of sustainability external costs on the design and management of the multimodal logistic network under analysis is emphasized. Full article

An “island formation” is a region within the hinterland of a port which is served by another port. Some regions of southern Europe, although located within the hinterland of some Mediterranean ports, are “island formations” of northern range ports (namely, northern European ports between Le Havre and Hamburg): an example is the Padan Plain, in northern Italy, which is currently, although only partially, an “island formation” of northern range ports. Actually, a relevant number of TEUs, which have origin or destination in the Padan Plain, and have been unloaded from ships operating deep-sea routes or will be loaded on them, cross northern range ports. Several sources report this number of TEUs, but there is disagreement among them. In this paper, firstly, this number of TEUs is estimated, according to scheduled rail connections between northern range ports and Italian intermodal centres/freight villages. Afterwards, an analysis of transport costs and travel times is carried out in order to determine the advantage of unloading containers (having origin in the Far East or North America and destination in the Padan Plain) through northern range ports instead of Italian ports. Full article

As one of main challenge for carriers, empty container repositioning is subject to various uncertain factors in practice, which causes more operation costs. At the same time, the movements of empty containers can result in air pollution because of the CO₂ emission, which has a negative impact on sustainable development. To incorporate environmental and stochastic characteristics of container shipping, in this paper, an empty container repositioning problem, taking into account CO₂ emission, stochastic demand, and supply, is introduced in a sea–rail intermodal transportation system. This problem is formulated as a chance-constrained nonlinear integer programming model minimising the expected value of total weighted cost. A sample average approximation method is applied to convert this model into its deterministic equivalents, which is then solved by the proposed two-phase tabu search algorithm. A numerical example is studied to conclude that the stochastic demand and supply lead to more repositioning and CO₂ emission-related cost. Total cost, inventory cost, and leasing cost increase with the variabilities of uncertain parameters. We also found that the total cost and other component costs are strongly dependent on the weights of repositioning cost and CO₂ emission-related cost. Additionally, the sensitivity analysis is conducted on unit leasing cost. Full article