Multimodal Container Research Articles

Path Optimization of Container Multimodal Transportation Considering Differences in Cargo Time Sensitivity

To optimize the container multimodal transportation path selection problem with differences in cargo time sensitivity, this paper introduces the concept of mixed time windows and establishes an integer programming model from the perspective of carriers. The objective is to minimize the total transportation cost while meeting the customer’s on-time delivery requirements. The model imposes hard time window constraints on cargoes with on-time delivery requirements and soft time window constraints on general cargoes. A bi-level genetic algorithm is employed to solve the model. A case study is conducted to demonstrate the effectiveness of the proposed approach. Experimental results show that the bi-level genetic algorithm’s convergence ability, efficiency, stability, and global search capabilities are far superior to those of traditional single-level genetic algorithms. This indicates that the use of multi-stage solution approaches can mitigate the shortcomings of genetic algorithms in dealing with high-dimensional problems. In addition, when analyzing the effects of time penalty intensity and time window on decision-making results, it is found that the more time-sensitive cargoes are more likely to be affected by the time window setting, and will tend to sacrifice costs to ensure that the time demand is met. At the same time an increase in demand for time-sensitive services is accompanied by an increase in operating costs. Accurate assessment and classification of time sensitivity of cargoes can effectively prevent wasting resources in unnecessary areas, and ultimately maximize decision outcomes and ensure the most efficient use of resources.

China-Europe Container Multimodal Transport Path Selection Based on Multi-objective Optimization

With the advancement of the "Belt and Road" initiative, trade between China and Europe has been steadily growing, and China-Europe container transportation has received increasing attention. This study analyzes the influencing factors of China-Europe container transport path selection and, based on the physical network of China-Europe container transport, constructs virtual nodes according to the transport modes that can be transited at different nodes and their own transshipment operations. By reflecting cost, time, and carbon emission factors in the virtual network, we construct a service network for China-Europe container multimodal transport, which in turn forms a multi-objective transport scheme selection model considering transportation cost, time, and carbon emissions. Subsequently, the economic and practical aspects of this transport path selection model are verified through five case studies of container transport from Dalian to Hamburg, Germany. Lastly, the sensitivity of factors, such as cost and time, to the China-Europe container multimodal transport path selection is assessed based on scenario analysis. This analysis offers valuable references for various decision-makers involved in the selection of the China-Europe container transport path.

Container Multimodal Cooperative Transportation Management Information System Based on Artificial Intelligence Technology

Artificial intelligence is a branch of computer science, which includes natural language, intelligent processing, and professional methods. Since the birth of artificial intelligence, the technology and application fields have continued to grow, and the application fields have also continued to expand. This article aims to study the application of artificial intelligence technology in the management information system of container multimodal transportation and to provide convenient and efficient operation methods for container multimodal transportation. This paper proposes the C-means clustering method. Through the research and development of the terminal management system, it has achieved great success in automation, intelligent planning, and integrated management. At the same time, the EDI system is adopted, which mainly uses the combination of GPS and GIS information platform Internet network technology. Therefore, when evaluating the operation of the multimodal transport virtual container under the control of coproduction, the DEA method is used to operate the multimodal virtual container. The situation is analyzed and evaluated, and the multimodal transport virtual container is determined through investment. The experimental results of this article show that the artificial intelligence system achieves the most efficient multimodal transport management with the most efficient system model, combined with the leading container multimodal transport virtual enterprise, to provide the best way of the management process for the development of the multimodal transport management information system. The intact rate of container cargo during transportation is as high as 99.7%.

Synergy Degree Evaluation of Container Multimodal Transport System

Logistics activities are an important source of energy consumption and environmental issues. Research conclusions and practical experience show that promoting the development of container multimodal transport is an effective way to reduce the level of carbon footprint. The key to influencing the development of container multimodal transport lies in the cooperation of all participants and links (modes of transport, transport businesses). Evaluating the synergy degree is a key step in this development process. This paper takes the whole process of container multimodal transportation as the research perspective, analyzes the operation process, and treats the process as a production system composed of four subsystems: facilities and equipment, organizational management, business operations, and information interactions. Through in-depth interviews and an analysis of the academic literature and policy documents, we establish a synergy degree evaluation index system and measurement model of container multimodal transport based on synergy theory and case studies. The research results are consistent with the actual situation. From 2015 to 2018, the synergy of container multimodal transport system of China’s G port developed slowly, but generally moved in a more orderly direction.

Development Countermeasures on Container Multimodal Transport of Railway in China

With the national “One Belt and One Road” strategy put forward, multimodal transport has become the key to break through the bottleneck of China’s comprehensive transport service capacity. In order to speed up the construction of modern integrated transportation system and promote the logistics industry to reduce costs and increase efficiency, this paper analyses the problems existing in the development of China’s railway multimodal transport and analyses the opportunities for the development of China’s railway container multimodal transport from four aspects. Finally, the paper puts forward some countermeasures for the development of multimodal transport, which can improve the efficiency of multimodal transport organization, realize the smooth connection of different modes of transport, and promote the cost reduction and efficiency increase of logistics industry.

The Study on the Optimization of Container Multimodal Transport Business Process in Shandong

Shandong is a coastal city with good location advantages. As a hub port for international trade goods and a port of transhipment, shandong's demand for multimodal transport is more urgent. By selecting the suitable non-water port and the multimodal transport carrier to improve the efficiency of multimodal transport, the purpose of saving the time of logistics is achieved, thus reducing the logistics cost.It branch out through Shandongt, and it can reach the central region of China, can reach the Western remote area ,too. This paper puts forward the optimization scheme of the business process of container multimodal transport. The optimization of freight forwarding business process is analyzed. The multimodal transport model in Shandong was designed. Finally, the optimal approach of multimodal transport in Shandong is put forward.

Optimization on Combination of Transport Routes and Modes on Dynamic Programming for a Container Multimodal Transport System

Along with the swift boom of the carriage of container and logistic economy, multimodal transport becomes more and more important economically. Container multimodal transport is a form of combined transport organization aimed to optimize the overall cargo transport. The optimal organization of various transport modes in container multimodal transport system directly concern the time, cost and quality of the cargo transport. In order to describe the optimal organization problem, an optimization model based on dynamic programming is presented in the paper, and is satisfied with reality constraints. Then, a dynamic programming algorithm is proposed to obtain the optimal combination strategy of transport modes. Finally, an empirical study is used to show the feasibility and efficiency of the proposed model.

Path Optimization of Container Multimodal Transportation Based on Improved Genetic Algorithm

This paper mainly studies on the optimization and algorithm of multimodal transport path. The algorithm considered the transportation time, freight, the different transport ways, and the possibility of occurrence of facelift premise between each node. All of this determined the best path and the mixture of intermodal transport, which minimize the total freight fee. Take the complexity of multimodal optimization into account, this paper optimized the genetic algorithm to transport scheme. The certain population of crossover and mutation rules in application will continue to evolve by coding each path, finally achieve the solution of concrete steps.