Intermodal Transportation Network Research Articles

Sustainable-resilient seaport-dry port network design considering inter-modal transportation

This paper proposes a multi-objective mathematical model for designing an inter-modal transportation network that includes a seaport and multiple dry-ports in both export-oriented and import-oriented modes under sustainability and resilience criteria. A multi-objective particle swarm optimization algorithm is tailored to solve the large-sized instances. The model and its solution method are validated through several numerical examples in different sizes whose results demonstrate that the development and design of such a seaport-dry port network is a critical component of the government's economic development while its development is a challenging issue requiring proper financing.

A multi-objective optimization approach for disruption management in an intermodal freight transport network

The growing demand for freight transportation is leading to pay more attention to the management of intermodal freight transport network (IFTN). The optimization of IFTN management will have many benefits in terms of sustainability, reducing costs and pollution. Although many studies on the optimization of IFTN operations exist, the management of disruptions deserves a particular attention since disruptions may lead to a significant drop of performance in the entire network. In particular, seaport terminals are prone to disruptions because of their key role in connecting the land side and the sea-side operations. The availability and reliability of the entire network is directly affected by their disruptions. In this paper, a multi-objective linear programming model is developed to minimize congestion in an IFTN, which is originated from the occurrence of a disruption in a seaport terminal. The model aims to minimize cost and emissions, simultaneously. Computational results of a realistic case study, inspired by an Italian IFTN, shows the effectiveness of the developed model to improve the performance of the entire network.

Gray Correlation Entropy-Based Influential Nodes Identification and Destruction Resistance of Rail-Water Intermodal Coal Transportation Network

Evaluating the importance of nodes in coal transportation networks and identifying influential nodes is a crucial study in the field of network science, vital for ensuring the stable operation of such complex networks. However, most existing studies focus on the performance analysis of single-medium networks, lacking research on combined transportation, which is not applicable to China’s coal transportation model. To address this issue, this paper first establishes a static topological structure of China’s coal-iron-water combined transportation network based on complex network theory, constructing a node importance evaluation index system through four centrality indicators. Subsequently, an enhanced TOPSIS method (GRE-TOPSIS) is proposed based on the Grey Relational Entropy Weight (GRE) to identify key nodes in the complex network from local and positional information dimensions. Compared to previous studies, this research emphasizes composite networks, breaking through the limitations of single-medium network research, and combines gray relational analysis with entropy weighting, enhancing the objectivity of the TOPSIS method. In the simulation section of this paper, we establish the model of China’s coal-iron-water combined transportation network and use the algorithm to comprehensively rank and identify key nodes in 84 nodes, verifying its performance. Network efficiency and three other parameters are used as measures of network performance. Through simulated deliberate and random attacks on the network, the changing trends in network performance are analyzed. The results show that in random attacks, the performance drops to around 50% after damaging nearly 40 ordinary nodes. In contrast, targeting close to 16 key nodes in deliberate attacks achieves a similar effect. Once key nodes are well protected, the network exhibits a certain resistance to damage.

Improving resilience in an intermodal transport network via bulk cargo transport coordination and empty container repositioning

Commodities are usually transported in bulk and are associated with the risk of environmental pollution and cargo loss during intermodal transportation. This study discusses the containerization of bulk cargo with the coordination of bulk cargo transport and empty container repositioning. In such a transport network, a bulk cargo transportation company can use empty containers to load and deliver bulk cargo. We proposed models to analyze the optimal decisions regarding the number of leased empty containers under uncertain demand. We discussed three business modes to demonstrate the financial and resilience performance of bulk cargo containerization and supply chain coordination. Our results show that the trip-sharing mode can significantly increase the amount of bulk cargo containerization by reducing the transportation cost of empty containers that need to be repositioned. This model can help bulk cargo logistics companies determine the optimal number of released containers by considering profits and risk control. This study also sheds light on ways to promote supply chain resilience by incentivizing containerization and trip sharing.

Carbon peak simulation and peak pathway analysis for hub-and-spoke container intermodal network

The global consensus on carbon peak and carbon neutral goals extends to the transport sector. This paper provides a method for simulating the carbon emission peak time and peak value within a container intermodal network (CIN). Our approach commences by capturing the fundamental network elements, including nodes, routes, and freight flows, through intermodal network modeling. We then integrate a carbon emission model with scenario analysis, utilizing Monte Carlo simulation to predict the probability of the CIN's carbon emission peak time and value. Finally, using the Yangtze River Delta regional container intermodal network (YRD-CIN) as a case study, 15 scenarios are set up to explore the effects of intermodal transport network development on carbon peaks and peak times under varying conditions in the YRD region. The findings demonstrate the significant influence of modal transport shifts, network connectivity, and energy technology levels on the carbon peak in the YRD-CIN.

Reliable route planning and time savings in real-world urban intermodal transportation networks: Evidence from Hamburg, Germany

Reliable route planning and time savings in real-world urban intermodal transportation networks: Evidence from Hamburg, Germany

How will China–Singapore International Land–Sea Trade Corridor affect route choice behaviour? A discrete choice model

Under the government-to-government cooperation framework, the Memorandum of Understanding (MoU) on China–Singapore International Land–Sea Trade Corridor (C–S-ILSTC) between Singapore and Chongqing has been signed in 2018, with the objective to improve the connectivity between Southeast Asia and Western China region via the Beibu Gulf port. C–S-ILSTC provides a new and efficient intermodal freight transportation route choice, which is expected to reconstruct the regional intermodal container transportation network. In this study, we formulate a discrete route choice model based on stated preference survey to analyse the route choice behaviour between Southeast Asia and western China region under the intermodal container transport network with C–S-ILSTC. Based on the modelling results, we further discuss the impact of significant route choice influential factors, such as transit time, shipping fee, cargo type, historical experience of using the route, company size, annual throughput, and business area. In addition, descriptive statistics and word cloud analysis are provided to investigate respondents’ underlying attitudes on the most important route choice influential factors. Scenario analysis is further conducted to demonstrate the impact of subsidy on respondents’ willingness to switch to the newly introduced C–S-ILSTC for freight transportation. The results provide policy implications on improving the utilisation rate of C–S-ILSTC.

DIGITAL TWINNING AS A DECISION SUPPORT TOOL FOR RESILIENCE PLANNING OF COASTAL INTERMODAL TRANSPORTATION NETWORKS

Intermodal freight transportation networks (seaport-road-rail) constitute the economic backbone of coastal communities. From the current state of the literature, it is observed that despite their importance, intermodal transportation networks remain unserved with comprehensive tools that support high-level planning for resilience of existing and future infrastructure under hurricane scenarios. To address these gaps, this paper proposes the implementation of a decision support tool based on digital twinning, which is able to predict system performance in terms of resilience, given three main inputs: hazard intensities, budgetary constraints, and the characteristics and topology of the network.

Logistics hub location for high-speed rail freight transport with road-rail intermodal transport network.

In this paper, we propose a new freight mode to describe how the designed HSR freight train serve for express delivery. We introduce the functions of the hubs and design the hybrid hub-and-spoke network of road-rail intermodal transportation from the perspective of planners, which features as single allocation rule and configures varying levels of hubs. The problem is accurately described by a mixed integer programming model with the objective to minimize total construction cost and total operation cost. We develop a hybrid heuristic algorithm based on a greedy strategy to obtain the levels of hubs, customer allocation and cargo routing. Taking the example of HSR freight network consisting of 50 cities in China, numerical experiments are conducted on the basis of forecasting data from the real-life express market to obtain the hub location schemes. The validity of the model and the performance of the algorithm are verified.

Decision support algorithm for intermodal transport networks: Urban aerial cableway systems

We propose a decision support algorithm to solve the service policy of urban cableway systems, which are used as a transport mode to address the First-Last Mile problem for intermodal urban public transport networks. Our work develops a stochastic discrete-event model for computing the queuing performance of the public transport networks and evaluates the effects on the passenger waiting time over a commercial working day, considering different service policies: (i) previous policy; (ii) current policy; and (iii) proposed policy. We provide an embarking procedure for urban cableway lines to aid transport operators in managing queues on platforms during rush hours. Finally, a set of large-scale Monte-Carlo simulations was conducted using a real multimodal network of a large-size metropolitan city (3.8 million inhabitants) to evaluate the effectiveness of different service policies.

An empirical study of China–Singapore International Land–Sea Trade Corridor: Analysis from supply and demand sides

The China–Singapore International Land–Sea Trade Corridor (C-S-ILSTC) was officially proposed in 2018, under the government-to-government framework of the China–Singapore (Chongqing) Demonstration Initiative on Strategic Connectivity. C-S-ILSTC is expected to play an important role in the international trade and connectivity between Western China and Southeast Asia, where Chongqing serves as the logistics hub in Western China, and Singapore is a transshipment hub for Association of Southeast Asian Nations (ASEAN) region. This paper aims to analyse the newly formed intermodal freight container transport network in the context of C-S-ILSTC and China–Singapore/ASEAN region quantitatively from both supply and demand sides, and investigate C-S-ILSTC’s advantages and disadvantages. For the demand side analysis, the results show that the trade volume between China and ASEAN countries is forecasted to consistently increase in recent years, and the most commonly traded cargo types between China and ASEAN have also been identified. For the supply side analysis, we examine the infrastructure and development status of the essential nodes along C-S-ILSTC. In addition, we also compare C-S-ILSTC with the conventional intermodal container transport routes connecting Western China and Southeast Asia, and discuss the development prospect of C-S-ILSTC. The results of this study could provide policy implications for the development of C-S-ILSTC and the cooperation between China and ASEAN region.

A Sustainable Location Model of Transshipment Terminals Applied to the Expansion Strategies of the Soybean Intermodal Transport Network in the State of Mato Grosso, Brazil

The transport system is one of the main bottlenecks of the world’s largest producer and exporter of soybeans, Brazil. Long-distance truck transportation of grains increases costs, food waste, and CO2 emissions. To handle these problems, the Brazilian government seeks to expand the transportation system through the national transport logistics plan (PNLT), promoting efficient operations. Collaborating on the environmental aspect, this paper proposes sustainable logistic infrastructure for soybean transportation. Investigating the largest grain-producing state in the world, Mato Grosso (Brazil), we show the optimal location for capacitated transshipment terminals untangling the relationship between logistics and sustainability. Besides handling cargo truck costs and CO2 emission, the optimization model considers cities, road distances, transshipment terminals existents, terminals capacities, implementing costs, and locations near waterways and railways. In five scenarios with different combinations of waterways and railways, we contrast the cost of installing terminals and the total road distance traveled under different weights for the environmental components. The results indicate that it is possible to simultaneously obtain the minimum cost of installing transshipment terminals and to reduce emissions by 20% in all analyzed scenarios. We conclude that obtaining strategic solutions at lower costs can be combined with proper environmental responsibility. As contributions, the results allow for advances in the area of sustainable logistics, encouraging the development of new research in Brazil involving the dimensions of sustainability. In addition, the study supports the government’s strategic decisions regarding ongoing discussions on expanding the intermodal soy transport network in the country.

Risk Perceptions Using Urban and Advanced Air Mobility (UAM/AAM) by Applying a Mixed Method Approach

From a mobility rationale, advanced air mobility (AAM) and/or urban air mobility (UAM) claims a reduction in travel time with integration into intermodal transportation networks and a reduction in ground traffic congestion due to the current modal shift to air, ultimately contributing to more sustainable transportation. Starting in 2025, South Korea is planning to operate air taxis between International Airport and Seoul downtown. This study applied a mixed-method approach to identify barriers to the use of air taxis by investigating consumers’ risk perception of air taxis. A focus group interview yielded a scale with 18 items across five dimensions. Next, through exploratory factor analysis, the 18 items were reduced to 10 items across two dimensions: safety risk (6 items) and cyber risk (4 items). The findings of this study will offer practical guidelines for creating marketing tools and designing strategic management planning for air taxis. The risk perception using air taxis will assist with creating a more strategic and efficient business model that destination management organizations, developers, and policymakers can utilize.

Modeling the capacity of multimodal and intermodal urban transportation networks that incorporate emerging travel modes

Given the increasing prevalence of new urban transport modes such as ridesharing, e-hailing, and combined transport, it is essential to evaluate their effects on the capacity of transportation networks. Hence, this paper develops a novel transportation network capacity model to capture the travel behaviors of inter-multimodal mobility in an urban transportation system that incorporates emerging travel modes. The novel model is formulated as a bi-level programming problem, in which the lower-level model is a combined modal split and traffic assignment (CMSTA) problem based on mathematical programming. The CMSTA problem adopts the cross-nested logit model to account for intermodal travel behavior in the modal split phase and the path-sized logit model to account for route overlap in the traffic assignment phase. Moreover, the logit-based trip distribution model is used to capture the dispatch of the e-hailing traffic flow and the matching of ridesharing drivers with passengers. Besides, we consider flow interactions (e.g., cars and buses sharing the same link) in the road network. We customize a solution framework for solving this novel model that adopts the recently developed fast path-based algorithm with the Barzilai–Borwein stepsize strategy to efficiently solve the CMSTA problem, and derive a sensitivity analysis-based (SAB) algorithm to solve the entire bi-level programming problem. The effectiveness of the novel model is verified in numerical experiments that demonstrate the effects of intermodal transportation, e-hailing, and ridesharing on the capacity of a multimodal transportation network.

Optimizing Intermodal Transport and Hub Location Problem for ECOWAS in the Context of Improving Intra-African Trade

Trade within Africa is at an all-time low, with a lack of an optimal intermodal transportation network and a high cost of business serving as a deterrent to trade. This research studies Intra-African Trade within ECOWAS using a hierarchical spatial aggregation process to identify 27 nodes. Distance-based weighted centrality measures employed TOPSIS to model a ranked node centrality of Economic Community of West African States (ECOWAS) intermodal transport of railway, road, and waterway networks. The ten highest-ranking nodes identified from the mixed-integer linear program adopted as candidate hubs, thus selecting Ibeshe ferry terminal in Lagos and Tema Harbour in Accra for waterway; Thies, Ibadan, Conakry, Monrovia and Thies for railway; and Thies and Ibadan for road. We conclude with sensitivity analysis and a discussion of management implications for ECOWAS. This paper demonstrated that a limited number of transshipment hubs would encourage interregional trade and cut point-to-point transportation costs and lead to economic growth and development.

Impacts of COVID-19 pandemic on foreign trade intermodal transport accessibility: Evidence from the Yangtze River Delta region of mainland China.

We address the problem of the impacts of COVID-19 pandemic on foreign trade transport by introducing a foreign trade intermodal transport accessibility (FTITA) index. First, we present the definition of FTITA, which combines the convenience of transporting domestic cargoes to overseas regions by an international intermodal transport network and the trade attractiveness of the domestic cargoes in the overseas regions. Second, we analyze the path choice behaviors of domestic shippers and propose the measurement method of the FTITA index. Finally, using the 41 cities in the Yangtze River Delta region in mainland China as origins and eight overseas regions as destinations, we empirically analyze the impacts of COVID-19 pandemic on the FTITA. With the empirical study conducted in prepandemic and postpandemic years, we analyzed the overall trends of the FTITAs from the YRD region to eight overseas regions, spatial patterns of the distributions of the FTITAs in the YRD region, rankings of average FTITA values for the top ten cities in the YRD region, and the FTITAs for different cargoes. The results indicate that the FTITAs of the YRD region in the prepandemic year are significantly higher than those in the postpandemic year. Moreover, in both the prepandemic and postpandemic years, the FTITAs to North America, Japan/South Korea, Europe, and Southeast Asia are significantly higher than those to Oceania, Middle East, South America, and Africa. Through analysis of the spatial patterns of the FTITAs across cities in the YRD region, we find that the cities with high FTITA are mainly close to Shanghai Port and Ningbo Port; the cities with middle-high FTITA are mainly located in southern Zhejiang and the regions along the Yangtze River; the cities with middle-low FTITA are mainly located in northern Jiangsu; and the cities with low FTITA are located in northern Anhui. Furthermore, comparing the impacts of COVID-19 pandemic on the FTITAs for different cargoes, we observe that COVID-19 has the least impact on foodstuffs and event cargoes. Our findings can guide decision makers in implementing policies for alleviating the impacts of COVID-19 pandemic on foreign trade transport and further promoting the sustainable development of port and shipping industries.

Distributed model predictive control methods for intermodal transport cooperative planning based on ADMM

The cooperative planning in intermodal transport networks can obtain the global optimal decision under the premise of ensuring the data privacy of each role in the cooperation and avoiding massive data transmission. For the control of container flow in intermodal transport networks, the distributed model predictive control (DMPC) method can effectively realize cooperative planning, but the convergence speed of the existing DMPC methods is slow. Therefore, this study attempts to construct faster DMPC methods for cooperative planning. The Jacobi proximal distributed model predictive control (JP-DMPC) and dual consensus distributed model predictive control (DC-DMPC) methods are constructed for container flow control based on two variants of alternating direction method of multipliers (ADMM). The simulation experiments prove that the convergence speed of JP-DMPC and DC-DMPC methods is higher than that of the state-of-the-art method on the premise that the time cost and interaction data volume of each iteration do not change much, and the DC-DMPC method improves planning speed particularly significantly. This study provides new methods for intermodal transport cooperative planning and has significance for the development of synchromodal transport.

A Sustainable Intermodal Location-Routing Optimization Approach: A Case Study of the Bohai Rim Region

The optimal intermodal nodes and routes are two of the most challenging issues for intermodal participants. We present a two-phase approach that includes the fuzzy c-means clustering method (FCM) and a multi-objective optimization model to solve intermodal location-routing issues. A weighted sum technique and a genetic algorithm (GA) are designed to address this model. The two-phase approach is beneficial in meeting different market demand preferences of intermodal participants. It also has applications in solving the sustainable intermodal location-routing problems, further solving the network optimization problem in large-scale scenarios. A typical intermodal transport network in the Bohai Rim region is used to verify the effectiveness of this approach. The results provide references for the participants in the Bohai Rim region to choose the optimal intermodal nodes and routes. The findings also offer theoretical insights for optimizing intermodal networks in other regions of China, with goals of improving sustainable transport efficiencies.

Synchromodal Transportation Analysis of the One-Belt-One-Road Initiative Based on a Bi-Objective Mathematical Model

Synchromodality is the key to finding sustainable solutions for logistics, especially across larger networks. The era of the COVID-19 pandemic has brought special attention to the disruptions in demand and supply across the world and has accentuated the need for sustainable transportation networks to handle such anomalies in supply chains. The proposed research develops a mathematical model for an intermodal transportation network and investigates the model on one of the largest and most widely discussed supply chain projects of the One-Belt-One-Road (OBOR) initiative. The proposed bi-objective model focuses on time and cost functions with rail, roads, and ships as modes of transportation. A detailed analysis was performed on various mode alternatives and links to evaluate their performance. The study provides an insightful understanding of the network with several suggestions. In contrast to roads and trains, container ships depict a fourfold increase in fuel consumption for an average ship weighing 4500 TEUs with the increase in shipping speed. It was concluded that increasing port capacity and reducing custom clearance time can have a major impact on lead times, and this is directly influenced by a country’s ease of doing business. Moreover, with its several branches, the OBOR initiative can provide a robust supply chain with increased logistical capacity.

Designing sustainable intermodal freight transportation networks using a controlled rail tariff discounting policy – The Iranian case

• A sustainable Intermodal Freight Transportation Network is developed. • The government determines a controlled rail tariff discount for rail companies and compensates the money that they lose due to offering the rail tariff discount by the money that will be collected from fuel saving in road freight transportation system. • The rail tariff discount is customized to the network’s OD flows and rail connections. • Multiple users’ route choice behaviors is modeled by applying a stated preference method. • A real case is studied and some insights are presented. Moving freight by intermodal services instead of road services not only saves a large amount of fuel but also improves sustainability. This paper presents a sustainable Intermodal Freight Transportation Network Design Problem (IFTNDP) in which the effectiveness of a new short-term policy, called controlled rail tariff discounting policy, is evaluated. In the IFTNDP, the government locates intermodal hubs and cooperates with rail companies to offer discounted rail tariffs on the rail connections of intermodal routes. Rail companies are allowed to customize the amount of rail tariff discounting for the network’s OD flows and rail connections. In addition, the government compensates the losses that rail companies incur due to offering the rail tariff discounts by the amount that will be collected from fuel savings in the freight transportation system. Hence, the government can boost the utility of intermodal transportation without investing funds to compensate the losses of rail companies. A stated preference model based on a questionnaire is adapted to identify users’ route choice behaviour. Then, the users’ route choice behavior is incorporated into the IFTNDP by a set of constraints, depending on the road and intermodal travelling times and costs. The model is applied to a real freight network and insights made by undertaking sensitivity analyses. The results demonstrate that the controlled rail tariff discounting policy not only increases the contribution of freight intermodal transportation in moving total freight but also enhances government’s profits from fuel savings after compensating rail companies’ losses.