Container Multimodal Transport Research Articles

Flexible yard crane scheduling for mixed railway and road container operations in sea-rail intermodal ports with the sharing storage yard

The sea-rail intermodal port, serving as the “cornerstone” supporting the seamless connection of landside and quayside transportation, plays a crucial role in determining the service level of the container multimodal transport through port’s operational organization efficiency. With on-dock rails, the physical integration between railways and water transport is smoothly achieved. However, within the port, the diversity in container flows adds complexity to operational organization and decision-making. In this paper, we formulate a flexible crane scheduling model to reduce the mutual interference during the mixed operations of railway containers and road containers in the sharing yard. The model addresses the time window constraints of railway containers required by train schedule, and the uncertain scenarios of external truck arrivals. To solve this problem, we design a two-stage approach that encompasses a task reassignment phase and a sequential decision-making phase. Furthermore, we test the model and algorithm performance through various experiments of different scales. Our results show that the designed algorithm designed solves instances of 20 tasks in 18.7 s, compared to 3600 s for the model solver. It efficiently handles real-world instances with over 200 tasks and 100 scenarios. Finally, sensitivity analysis is carried out to capture the influence of railway container ratio, truck arrival patterns, and train time windows on yard operations. Under intensive operation, we find that road containers, following a uniform arrival pattern, are least affected by railway container operations when the proportion of railway containers in the sharing block ranges from 70% to 80%. We also observe that the flexibility of crane service increases as the time window for railway container operations becomes more lenient.

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.

Trapezoidal cloud based heterogeneous multi-criterion group decision-making for container multimodal transport path selection

Due to the rising globalization of the economy, a single container transportation mode can no longer meet the requirements of global supply chain management. This article proposes a new method combining trapezoidal cloud and MULTIMOORA (Multi-Objective Optimization on the basis of Ratio Analysis plus full multiplicative form) for heterogeneous multi-criterion group decision-making (HMCGDM) to determine the optimal path of container multimodal transport. Firstly, in order to represent the ambiguity and uncertainty of path evaluations, this article uses heterogeneous information to represent the assessments and puts forward some new methods to convert different forms of linguistic evaluation information into trapezoidal clouds. Second, decision makers’ (DMs’) weights are determined through internal weights and external weights. Third, the similarity of trapezoidal clouds is determined by calculating the overlapping area, the criterion weights are objectively obtained by calculating the similarity of trapezoidal clouds under different situations. Fourth, based on MULTIMOORA, a new ranking index is defined to determine the optimal alternative. Thereby, the proposed method for HMCGDM is described step by step. Finally, a real case study of container multimodal transport path selection is analyzed to demonstrate the practicality of the proposed method. The findings of sensitivity and comparative analyses verify the robustness and advantages of the proposed method.

Optimization of intermodal routes for reefer containers under double uncertainty

Aiming at the influence of demand uncertainty and stochastic carbon trading price on the choice of intermodal transportation route for reefer containers, a hybrid robust stochastic optimization model with minimum economic cost is established, and a Monte Carlo sampling-based catastrophic adaptive genetic algorithm is designed to test the reasonableness and validity of the model. The results show that: influenced by the regret value constraint, the robust optimization of demand uncertainty will increase the total cost of reefer container multimodal transportation, while the increase of carbon trading price stochasticity doesn’t necessarily mean the increase of cost, and the reasonable setting of carbon trading price stochasticity and the trade-off between the maximum regret value and the economic cost, so that the cold-chain logistics and transportation enterprises can easily deal with the fluctuation of the demand of the freight transportation market, and also respond to the low-carbon requirements.

Multimodal container schemes freight delivery

The article highlights the topical issue of the development of container multimodal transport, which is a priority in the development of transport services; their use will increase the volume of cargo delivered to the destination by the most efficient modes of transport (their combination). Container transportation of goods significantly reduces the cost of delivery of goods from producers to consumers. Container transportation has become the most economical without transshipment technology and, above all, in the intercontinental multimodal land-sea service. The work aims to study the practical aspects and substantiate practical recommendations for the logistics of multimodal container transportation of goods in global supply chains. Conduct a comparative analysis of implementing multimodal container traffic in different containers, namely 20 and 40 feet. The analysis and calculations of the data of container transportation processes for the conditions of two international transport corridors, TRACECA and the trans-Caspian international transport route, are carried out. The cost of transportation by sea, although their number is small relative to the total share of routes, significantly affects the total cost of transportation. In order to stimulate freight traffic on these routes, member states have set discounts of up to 10% of the cost of the ferry fare. Studies suggest that the use of multimodal container traffic is currently economically feasible. The conducted research of practical aspects and substantiation of practical recommendations on logistics of multimodal container transportation of goods in global supply chains suggests that container transportation is a way of delivery today using multimodal options for delivery of goods. An in-depth comparative analysis of implementing multimodal container traffic in different containers, namely 20 and 40 feet, allows us to conclude that using the Trans-Caspian International Transport Route (TMTM) with a 20-foot container is more economically attractive and can be recommended. Keywords: container transportation, supply chains, logistics, international transport corridors, multimodal transportation.

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.

A heuristic algorithm for equipment scheduling at an automated container terminal with multi-size containers

With the increasing volume of shipping containers, container multimodal transport and port scheduling have attracted much attention. The allocation and dispatching of handling equipment to minimize completion time and energy consumption have always been a focus of research. This paper considers a scheduling problem at an auto-mated landmaritime multimodal container terminal with multi-size containers, in which operating facilities and equipment such as quay cranes, vehicles, yard cranes, and external container trucks are involved. Moreover, the diversity of container sizes and the location of handshake areas in yards are concerned. A mixed integer program-ming model is established to schedule all operating facilities and equipment. To solve the mathematical model is a NP-hard problem, which is difficult to be solved by conventional methods. Then we propose a heuristic algorithm which merges multiple targets into one and designs an improved genetic algorithm based on the heuristic combi-nation strategy in which 20-ft containers are paired-up to the same yard before allocation. After that, some exper-iments are designed to prove the effectiveness of the model and the algorithm. The effect of configurations on efficiency and energy consumption under different conditions is discussed, and the influences of different parame-ters and the proportion of 20-ft containers are also compared. Furthermore, the influence of locations of hand-shake area with different yard quantities are compared. To conclude, there is an optimal number of equipment to be allocated. If few equipment is used, the operation time will be prolonged; if too many, the energy consumption will be increased. When the yard operation is the bottleneck, the handover location should be in the centre, other-wise other locations might be feasible. When the proportion of 20-ft containers that can be combined is large, the method proposed in this paper has advantages over traditional methods. The proposed algorithm has made a breakthrough in improving efficiency and reducing energy consumption.

Multimodal Transportation Route Optimization of Cold Chain Container in Time-Varying Network Considering Carbon Emissions

To solve the multimodal transport route optimization problem considering carbon emission, the vehicle speed has time-varying characteristics, and the customer has a time window limit. The carbon emission of multimodal transport system is affected by the energy consumption of transport vehicles in the time-varying network. The time-varying network is uncertain, and carbon emissions may continue to rise after a gradual decline. Based on this, this study established the sum of the carbon emission cost, transportation cost, penalty cost for exceeding the time window, and the damage cost of the cold chain cargo as the objective function. A route optimization model of cold chain container multimodal transportation was established. Static and dynamic optimization scenarios were designed and a hummingbird evolutionary genetic algorithm was used to solve the model. The effectiveness of the model and the practical value of the study are verified by the empirical analysis of the multimodal transport network of the Yangtze River Delta economic group. Results show that the dynamic model of the time-varying network can more truly reflect the transportation of the multimodal transport network and meet the efficiency requirements for the cold chain container multimodal transport. This study aims to solve the time-varying network under cold chain route optimization of container intermodal transportation, provides new insights for related businesses and a theoretical basis for reasonable multimodal transport route decisions.

Evaluation of the competitiveness of the container multimodal port hub

The research on the competitiveness of container multimodal transport port hub, comprehensively considering the software and hardware strength of port hub, is of great significance to analyze the specific source competitiveness of port hub, the optimal allocation of multimodal transport capacity resources and port operation management planning. Based on this, according to the principle of fuzzy set and membership function in fuzzy theory, this paper adopts the modeling method of multi-attribute decision-making to deeply analyze the key influencing factors of port hub competitiveness, extract the core indicators from the four aspects of business capacity, transport capacity resources, infrastructure and service quality, and then construct the fuzzy multi-attribute decision-making evaluation model of port hub competitiveness, and take the container transportation in Northeast China as an example. The research shows that the key influencing factors of multimodal transport port hub competitiveness have changed from traditional infrastructure factors to flexible influencing factors such as transportation service quality, transportation capacity and resource integration ability, transportation business efficiency, and port enterprises are in the critical period of industry transformation and upgrading. Strengthening inter industry integration, building industrial ecological alliance and building a multi-mode transportation integrated service chain with port as the core play an obvious role in promoting the formation of the core competitiveness of port hub. Among the ports along the coast of Liaoning, Yingkou Port has the strongest competitiveness against the supply of corn containers in Northeast China, and the competitiveness of other ports from strong to weak is Jinzhou port, Beiliang port, Panjin Port, Huludao port, Dandong port, Dalian port and Suizhong port. The research results enrich the theoretical system of multimodal transport port hub competitiveness research, and provide reference suggestions for port enterprises, transportation enterprises, government departments and other relevant subjects in strategy formulation, policy implementation, layout planning and so on.

Path Optimization of Low-Carbon Container Multimodal Transport under Uncertain Conditions

The development of multimodal transport has had a significant impact on China’s transportation industry. Due to the variability of the market environment, in this study, based on the context of the official launch of the national carbon emission trading market, the uncertainty of the demand and the randomness of carbon trading prices were considered. Taking minimum total transportation cost as the objective function, a robust stochastic optimization model of container multimodal transport was constructed, and a hybrid fireworks algorithm with gravitational search operator (FAGSO) was designed to solve and verify the effectiveness of the algorithm. Using a 35-node multimodal transportation network as an example, the multimodal transportation costs and schemes under three different modes were compared and analyzed, and the influence of parameter uncertainty was determined. The results show that the randomness of carbon trading prices will lead to an increase or decrease in the total transport cost, while robust optimization with uncertain demand will be affected by the regret value constraint, resulting in an increase in the total transport cost. Multimodal carriers can reduce transportation costs, reduce carbon emissions, and improve the transportation efficiency of multimodal transportation by comprehensively weighing the randomness of carbon trading prices, the nondeterminism of demand, and the relationship between the selection of maximum regret values and transportation costs.

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%.

Cost Analysis of Multimodal Transport on Refrigerated Container

Refrigerated container multimodal transport is a long-distance interprovincial transportation, which effectively ensures the quality of agricultural products. The application of refrigerated containers and other means of transportation in the long - distance transportation of perishable agricultural products can reduce the cost of multimodal transport of agricultural products and improve the logistics efficiency. Therefore, it is of practical significance to study the multimodal transport cost analysis of refrigerated containers for perishable agricultural products. The article classifies the applicable goods in refrigerated containers and refrigerated containers; Erishable agricultural products have short shelf life and high damage rate. Refrigerated transportation tools have the particularity; In the cold chain logistics environment, in addition to considering the transportation cost, transit cost and time penalty cost of normal temperature multimodal transport, we should also consider the loss cost of perishable agricultural products in transit and the energy loss cost of refrigerated container refrigeration in transit.

Synergy evaluation model of container multimodal transport based on BP neural network

With the rapid development of economic globalization, the trade of various countries has become increasingly close and thus the rapid growth of container transportation business. The rational choice of transportation routes and intermodal transportation methods has become a hot topic in this field. In order to improve the efficiency of intermodal transportation and reduce the cost of intermodal transportation, this paper studies the evaluation of the synergy effect of container multimodal transportation based on the BP neural network algorithm. First, it is determined that the multi-attribute decision-making method is used to comprehensively evaluate the synergy effect of container multimodal transportation, and the data are normalized. Select the appropriate hidden layer nodes, use Matlab to determine the learning rate, select the logsig function for the network transfer function, select Traingdx as the training function, and establish a container multimodal transport synergy evaluation model based on BP neural network. Secondly, the model is solved, and the problem is transformed into finding the shortest route from Q to P without exceeding the cost and time constraints. Then carry on the simulation experiment, use Matlab to solve the transportation time and total cost between cities. Experimental data show that when the number of iterations is 800, the algorithm begins to converge; at the fifth training, the error between the actual output and the expected output is only 0.0004; in route B, the time of multimodal transportation is 48.18% less than that of single transportation, and the cost is saved by 50.02%. This shows that the container multimodal transport synergy evaluation model based on BP neural network can accurately evaluate the effects, and container multimodal transport can indeed improve transportation efficiency and save costs.

MULTIMODAL CONTAINER SCHEMES FREIGHT DELIVERY

Summary. The article highlights the topical issue of development of container multimodal transport, which are a priority in the development of transport services, their use will increase the volume of cargo delivered to the destination by the most efficient modes of transport (their combination). Container transportation of goods significantly reduces the cost of delivery of goods from producers to consumers. Container transportation has become the most economical without transhipment technology, and, above all, in the intercontinental multimodal land-sea service. The aim of the work is to study the practical aspects, substantiate practical recommendations for the logistics of multimodal container transportation of goods in global supply chains. Conduct at comparative analysis of the implementation of multimodal container traffic in different containers, namely 20 and 40 feet. The analysis and calculations of the data of container transportation processes for the conditions of two international transport corridors: TRACECA and trans-Caspian international transport route are carried out. The cost of transportation by sea, although their number is small relative to the total share of routes, significantly affects the total cost of transportation. In order to stimulate freight traffic on these routes, member states have set discounts of up to 10% of the cost of the ferry fare. Studies suggest that the use of multimodal container traffic is currently economically feasible. The conducted research of practical aspects and substantiation of practical recommendations on logistics of multimodal container transportation of goods in global supply chains suggests that the use of container transportation is a way of delivery today using multimodal options for delivery of goods. An in-depth comparative analysis of the implementation of multimodal container traffic in different containers, namely 20 and 40 feet, allows us to conclude that the use of the Trans-Caspian International Transport Route (TMTM) with a 20-foot container is a more economically attractive option and can be recommended.

Retracted: Emergency Decision Support System for Container Logistics Safety Based on Image Processor

Container multimodal transport is the main transport mode and development trend of international logistics. Information system plays an important role in the development of multimodal transport and is an important part of regional multimodal transport network layout. Due to the influence of global economic integration and borderless logistics, the improvement of logistics efficiency depends more on information management technology. Based on the research results at home and abroad, this paper introduces the image processing system, and establishes the research model of container multimodal transport logistics security emergency decision support system based on image processor by using mathematical modeling optimization method, summary and induction method, and the combination of qualitative analysis and quantitative analysis method Based on the theory, early warning management method and emergency decision system, an emergency decision support system for container multimodal transportation logistics safety based on image processor is established. This study is prospective. The results show that the overall efficiency is improved by 20% and the overall efficiency is higher after using the method in this paper, which has certain practical value.

Coastal container multimodal transportation system shipping network design—toll policy joint optimization model

A coastal container multimodal transportation system has two modes of transportation, i.e., land and water. Due to economies of scale, the latter has become an emerging way to decrease the pollution of the system. This paper establishes a programming model to improve the system’s sustainable transportation policy. The model aims to minimize the carbon dioxide emissions of the system by optimizing two types of policies (i.e., a shipping network design policy and a toll policy) simultaneously. A local optimization algorithm is proposed to solve the abovementioned model. Real-world data on container transportation in the Bohai Rim in Northeast China are used to perform two sensitivity analyses. The running time of each calculation experiment does not exceed 2 minutes, showing the efficiency of the aforementioned algorithm. The experimental results show that the policies can reduce carbon dioxide emissions from container transportation in Bohai Rim from 3.29% to 6.70% under different scenarios. The diminishing marginal utility of the government’s sustainable policy is also revealed.

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.

Using mixed methods to design service quality evaluation indicator system of railway container multimodal transport.

Multimodal transport can bring the technical and economic advantages in different transportation modes into full play. While ensuring the level of service, it can reduce energy consumption and transport costs. Governments of most countries are actively promoting it. Therefore, it has become a research hot spot. Being a green, fast, and all-day transport mode, railways play an important role in multimodal transport. This article aims to analyze a multimodal transport service quality indicator system involving railways from the perspectives of customers, multimodal service providers, and governments. Qualitative and quantitative research methods were adopted to analyze the secondhand data of academic papers, government policy, and industry reports to clarify the quality characteristics of multimodal transport services. Using grounded theory and to analyze firsthand data from in-depth interviews with multimodal transport practitioners, 25 evaluation indicators of container multimodal transport service quality were chosen to be the evaluation index system. To test and improve the evaluation scale, 270 valid questionnaires were analyzed using SPSS 24.0 and AMOS 21.0 software, including reliability analysis, exploratory factor analysis, and confirmatory factor analysis. The results show that all the indicators meet the standard requirements and have good reliability and validity.

A two-stage model for an urban underground container transportation plan problem

As a new transportation mode, underground logistics system can be used as one of the solutions to alleviate traffic congestion and air pollution on urban roads. In this paper, an underground container transport system is designed to realize the road-underground-ocean container multimodal transport. This paper first analyzes the multi-stage decision-making content needed to design the underground container transportation system from the functional point of view of transporting a container. Then a two-phase model is built. The first stage is a 0–1 planning model with the lowest single-container cost to determine the planning layout and the second stage is to construct a simulation model under the current scenario to simulate the volume of transport containers within a specified time. Finally, a case study was carried out to determine the effectiveness of the method.

Study on Income Distribution Model of Container Multimodal Transport

The income distribution scheme is the premise of the smooth operation of enterprise alliance of container multimodal transportation. The goal of multimodal transport is to better integrate the various modes of transport organization and provide convenient transport services. The alliance enterprise puts forward the distribution scheme of self-interest from the point of view of maximizing its own income, while the multimodal transport operator guides the member enterprises to choose and modify the scheme, so that the distribution scheme can be accepted by all members. This paper analyzes the main body of income distribution on container multimodal transportation,and analyzes the principles of cooperative game income distribution,and puts forward two modes of income distribution on container multimodal transportation, and finally puts forward the distribution income scheme of container multimodal transportation.