Search Results (24)

According to the Formula 1 commitment to produce net zero carbon emissions by 2030, the present paper examines the environmental impact of Formula 1 logistics by means of a case study carried out from the point of view of an Italian company, with reference to the European Grand Prix. Logistics accounts for approximately 49% of the sport’s total emissions and accordingly, to reduce its carbon footprint, addressing the logistics activity is vital. Two scenarios are compared in detail: AS-IS, involving only road transport of assets, and TO-BE, in which a combined rail–road approach (i.e., intermodal freight) is implemented. While the AS-IS scenario is more cost-effective, it has a significant environmental impact in terms of CO₂ emissions; in contrast, though more complex and costly, TO-BE offers major advantages for environmental sustainability, including reduced emissions (approximately half compared to AS-IS) and improved efficiency through intermodal transport units. This study stresses that a combined transport system, facilitated by the European rail infrastructure, is a more sustainable option for Formula 1 logistics. However, achieving full carbon neutrality still represents a challenge that will require further innovations and collaboration among the stakeholders of this world. Full article

Existing research concentrates on analyzing the propagation and recovery of complex network risk or failure under a single model, which makes it difficult to effectively deal with the chain reaction. Concerning the recovery delay caused by the risk–failure interactions, this paper proposes a model for the propagation and recovery of risk–failure interactions. This model not only considers the network risk–failure interactive propagation mechanism but also introduces the load-balancing strategy and repair mechanism. The study quantifies the impact of the station on network resilience after different attack modes. In addition, the resilience metrics based on the station failure are established to accurately represent the resilience evolution of the network during propagation and recovery. Finally, focusing on the Belt and Road transportation network, we explore the evolution of network resilience under the variation of failure station repair time, station risk state recovery rate, and hub station allocation parameters. The simulation results showed that the model reduced the resilience loss through resilience recovery and accelerated the network back to normal in the face of attacks, shortening the station repair time and increasing the station risk recovery rate significantly improved the overall resilience level of the network, and increasing the proportion of hub station balancing based on the residual capacity effectively improved the minimum resilience of the sea–rail intermodal transportation network. Full article

Deciding on appropriate transport modes is critical in terms of emissions, time, and cost. However, transport routes do not always allow for the selection of the most cost-effective and environmentally friendly modes of transport. Therefore, various modes of transportation must be used together to overcome these constraints. This study investigates the use of a combination of different transportation modes in container transport from Filyos in Turkey to Vienna. Constanța has been selected as the trans-shipment port on the transport route, and three distinct modes of transport have been used from Constanța to Vienna, including road, rail, and riverway. As a result of this study, the fuel consumption, CO₂ emissions, time, and cost for each intermodal transport type were evaluated comparatively. Although seaway transportation is advantageous in terms of emissions, cost, and fuel consumption, it is determined that road transport is more beneficial in terms of time. The maximum and minimum CO₂ emissions were calculated to be 2,107,124 tonnes and 365.6 tonnes for roadway and seaway transportation, respectively. Full article

A cheap, easy-to-build basic module and multiplatform configurations obtained by connecting basic modules with dimensions corresponding to typical rail containers (10-foot, 20-foot, or larger) can be used to support intermodal rail-road transport of wooden and metal logs, including pipes, products transported on pallets and loose materials. This paper presents assumptions of the hybrid numerical research method and selected aspects of numerical strength tests of platform-containers in the basic 10-foot configuration. Multibody analyses (MBS), the finite element method (FEM), the original methodology, and various class mathematical models of the tested platforms were used appropriately in numerical tests. In the analysis of the results of multi-variant tests with the use of maximum operating loads, special attention was paid to the stress exerted on the joints between the movable components of the intermodal platform. Full article

Aggregates are the second-most consumed product in the world after water. This geological resource is used as building and construction material, and its production in quarries and delivery to customers generates several environmental problems. Their transport from quarries to consumption points, almost entirely done by truck, also generates impacts such as an increase in traffic and noise and the emission of greenhouse gases and other pollutants. Transportation and storage of goods account for 15% of greenhouse gas emissions in Europe and will increase significantly by 2050. To mitigate this, the European Union suggested shifting 30% of long-distance road freight to cleaner alternatives, such as rail or waterborne transport. This approach neglects the enormous volume of short-distance freight movement and its impact on achieving the goal of reducing greenhouse gas emissions. In this study, the hypothesis to test is whether the use of an intermodal rail/road transport mode, instead of just roads, for the transport of some products can help reduce global CO₂ emissions even for short distances. To test this, this study investigates the carbon emissions (and transport cost reduction) generated by rail/road intermodal aggregate transport for short distances in the Madrid region (Spain), rather than the currently used direct truck transport. An analysis of variables, such as aggregate supply, demand locations and amounts, and road and rail networks, using a geographical information system provides the associated carbon emissions of the different transport alternatives. To obtain a reduction in CO₂ emissions, this study proposes the establishment of intermodal transfer facilities near consumption centers, where materials are primarily transported by rail, with road transport limited to the final delivery to consumption areas. The results anticipate a notable decrease in carbon emissions in aggregate transport and allow the establishment of more efficient and environmentally friendly rail/road intermodal transport that would help to meet the goals of reducing climate change while making the use of aggregates more environmentally friendly. Full article

This study focuses on the ‘short-inverted transportation’ scenario of intermodal transport. It proposes a vehicle unloading reservation mechanism to optimize the point-of-demand scheduling system for the inefficiency of transport due to the complexity and uncertainty of the scheduling strategy. This paper establishes a scheduling strategy optimization model to minimize the cost of short backhaul and obtain the shortest delivery time window and designs a hybrid NSGWO algorithm suitable for multi-objective optimization to solve the problem. The algorithm incorporates the Non-dominated Sorting Genetic Algorithm II (NSGA-II) algorithm based on the Grey Wolf Optimizer (GWO) algorithm, compensating for a single algorithm’s premature convergence. The experiment selects a logistics carrier’s actual road–rail intermodal short-inverted data and compares and verifies the above data. The results show that the scheduling scheme obtained by this algorithm can save 41.01% of the transport cost and shorten the total delivery time by 46.94% compared with the original scheme, which can effectively protect the enterprise’s economic benefits while achieving timely delivery. At the same time, the optimized scheduling plan resulted in a lower number of transport vehicles, which positively impacted the sustainability of green logistics. Full article

Road–rail intermodal transportation (RRIT) leverages the advantages of multiple transport modes and is crucial for addressing the current issue of imbalanced development in the transportation sector. However, passengers’ behavior in choosing RRIT remains unclear, and it is necessary to optimize travel service quality through analyzing RRIT choice behavior based on user perceptions. This study designed a stated preference experiment that included both direct and multi-modal travel options. A hybrid choice model considering attitude variables was constructed, and four latent attitude variables—convenience, economy, comfort, and riskiness—were extracted to analyze their impact on intercity travel mode choice behavior under conditions of ticket booking uncertainty. The results revealed that the ticket booking success rate is a critical factor in travelers’ decision-making. Passengers tend to choose travel options with higher ticket booking success rates, even if it entails a slight increase in the ticket prices for the high-speed rail to high-speed rail transfer option. The attitude variables significantly influence intercity travel mode choice behavior, with travelers generally exhibiting a preference for risk avoidance in their travel options. Moreover, there are differences among various groups of travelers in their preferences and demands for the convenience, economy, and comfort aspects of travel options. These research findings can enhance our understanding of the key factors influencing the selection of RRIT services, thereby supporting RRIT designers and planners in improving service quality and facilitating the future growth of RRIT. Full article

This paper aims to contribute to the process of evaluating urban rail infrastructure projects through the presentation of the methodology and the results of a preliminary feasibility study concerning the revitalization, development, and (re)integration of the rail with road, maritime, and air transportation in the Zadar urban area. The analysis included the identification and evaluation of rail infrastructure alignment variants that would ensure the revitalization of the existing railway infrastructure, relocation of freight rail traffic from the narrow and densely developed suburban coastal area, promotion of intermodal passenger and freight transportation, improvement of urban and regional accessibility and connectivity, increase of traffic safety, reduction of travel time and operating costs, and decrease of traffic impacts on the environment. By consulting legal frameworks, spatial planning documentation, and analyzing the socio-economic context and existing transportation infrastructure function, six variants for the (re)development of the rail infrastructure were designed. As their design approached the area’s transportation issues from different angles and could contribute differently to the area’s economic, social, and territorial issues, a multi-criteria analysis supplemented with a partial cost–benefit analysis was conducted to select the most suitable variant. The evaluation was based on seven weighted criteria quantified by the normalization of 32 indicator values, scored from 1 to 5, where a score of 5 was considered the highest. Weighting the scores according to the ratios determined through a consultation process with stakeholders resulted in ranking the best variant with a total score of 3.7 and the worst one with a total score of 2.6. To avoid potential objections that the set of criteria weights used was subjective and the result biased, a sensitivity analysis was carried out by systematically varying the weights among criteria. The results showed that the best-ranked variant was also the least sensitive to applied weight shifts, with a score range of 0.2. Full article

Modern rail/road transportation systems are critical to global travel and commercial transportation. The improvement of transport systems that are needed for efficient cargo movements possesses further challenges. For instance, diesel-powered trucks and goods trains are widely used in long-haul unimodal transportation of heavy cargo in most landlocked and developing countries, a situation that leads to concerns of greenhouse gases (GHGs) such as carbon dioxide coming from diesel fuel combustion. In this context, it is critical to understand aspects such as the use of some parameters, variables and constraints in the formulation of mathematical models, optimization techniques and algorithms that directly contribute to sustainable transportation solutions. In seeking sustainable solutions to the bulk cargo long-haul transportation problems in Zambia, we conduct a systematic review of various transportation modes and related mathematical models, and optimization approaches. In this paper, we provide an updated survey of various transport models for bulk cargo and their associated optimized combinations. We identify key research challenges and notable issues to be considered for further studies in transport system optimization, especially when dealing with long-haul unimodal or single-mode heavy cargo movement in countries that are yet to implement intermodal and multimodal systems. Full article

This study explores a road–rail intermodal routing problem. To improve the carbon efficiency of transportation, reducing CO₂ emissions is considered by the routing. Soft time windows are incorporated into the routing to optimize the timeliness of the first-mile pickup and last-mile delivery services in intermodal transportation. The routing is further modeled in a time-dependent and fuzzy environment where the average truck speeds of the road depend on the truck departure times and are simultaneously considered fuzzy along with rail capacities. The fuzzy truck speed leads to the fuzziness of three aspects, including speed-dependent CO₂ emissions of the road, a timetable-constrained transfer process from road to rail, and delivery time window violation. This study formulates the routing problem under the above considerations and carbon tax regulation as a combination of transportation path planning problem and truck departure time and speed matching problem. A fuzzy nonlinear optimization model is then established for the proposed routing problem. Furthermore, chance-constrained programming with general fuzzy measure is used to conduct the defuzzification of the model to make the problem solvable, and linearization techniques are adopted to linearize the model to enhance the efficiency of problem-solving. Finally, this study presents an empirical case to demonstrate the effectiveness of the designed approach. This case study evaluates the performance of carbon tax regulation by comparing it with multi-objective optimization. It also focuses on sensitivity analysis to discuss the influence of the optimistic–pessimistic parameter and confidence level on the optimization results. Several managerial insights are revealed based on the case study. Full article

Foliated transport networks represent a concept that aims to improve the efficiency of the transport system by combining direct connections and hub and spoke design. In addition to combining these designs, a foliated transport network requires a high level of dynamic planning and control, as well as optimisation of goods and resources between the different network layers. It highlights the advantages of individual transport network designs and minimizes their weaknesses, ultimately leading to better performance of the foliated system than the individual options. The purpose of this paper is to describe the basic models of the freight transport network and the benefits of connecting these models. This survey paper aims to provide an overview of previous research in the field of foliated transport networks and to provide future research guidelines in this field that include the application of this model in intermodal transport. Full article

The sustainable performance of the intermodal transport chain has gained popularity in recent decades, especially due to climate change and numerous European laws aimed at minimizing the negative impacts of transport. In this paper, we have developed a novel three-phase, two-stage approach that is a combination of distance-based analytic hierarchy process/data envelopment analysis (AHP-DEA). The added value of this multi-criteria approach is in evaluating a sustainable intermodal transport chain, with prioritization of the most efficient combinations of transport in accordance with the weights derived from its users. Instead of the classic pairwise comparison, the weights of the criteria were determined using a new distance-based AHP method in which respondents were asked to sort the criteria (transportation time, price, emissions, and variability) pre-selected from the literature in order of greatest importance. Therefore, the approach determines the most efficient transport chain in the transportation corridor. Since a transportation corridor was previously defined, the settings for this corridor were set to constant initial variables. In this way, the above criteria were chosen as inputs, with DEA aimed at minimizing these variables and presenting the results in ranks from highest to lowest efficiency. The potential of our approach was presented in a case study, where the most efficient of the selected transport chains between Asia and the northern Adriatic were chosen. The results show that there are different intermodal transport chains, each of which consists of either maritime and rail transport or maritime and road transport. The paper concludes that the presented multicriteria approach has greater discriminatory power than the current DEA, as well as greater flexibility, since the weights can be derived faster and more effortlessly than is typical. Therefore, this method can help transportation organizers to determine which intermodal transportation chain is the most efficient or sustainable in any given situation. Full article

In the literature, hub-networks have often been modeled such as only one mode is considered for all transportation. Also, the consolidated demand flows are assumed to be transferred directly between each origin-destination hub pairs. The previous assumptions impose restrictions on the practical applications of such hub-networks. In fact, various transport modes are usually retained for freight transport, and intermodal terminals (e.g., rail terminals) may not realistically be fully connected. Thus, to assist decision makers, we investigate if the appropriate use of more eco-friendly transportation modes in incomplete networks may contribute to the accomplishment of the significant global reduction goals in carbon emissions. In this paper, we study the intermodal green p-hub median problem with incomplete hub-network. For each p located hub nodes, the hub-network is connected by at most q hub-links. The objective is to minimize the total transportation-based CO${}_2$ emission costs incurred through the road- and rail-transportation of each o-d demand flows. We present a MILP formulation for the studied problem and propose a novel genetic algorithm to solve it. A penalty cost is considered on solutions where train capacity is exceeded. Additionally, we present a best-path construction heuristic to generate the initial population. Furthermore, we develop a demand flows routing heuristic to efficiently determine the partition of demand flows in the incomplete road-rail network. And we implement novel crossover and mutation operators to produce new off-springs. Extensive computational experiments show that the proposed solution approach outperforms the exact solver CPLEX. Also, we perform a comparison between the unimodal and intermodal cases, and offer a discussion on the tuning of freight trains. Full article

Analyzing the efficiency of transport infrastructure connectivity and trade in the Regional Comprehensive Economic Partnership (RCEP) is very important for regional integration for international trade in the RCEP. This study aims to significantly measure the efficiency of the connectivity of infrastructure in the RCEP for improving the performance of infrastructure connection and suggest the way to improve the connection of infrastructure. Therefore, the input and output variables of infrastructure connectivity have been inserted to achieve this objective. The inputs are: the number of ports, rail range, and road networks, the number of land borders, the number of maritime borders, number of cross border points, railway linkage with other countries, number of ports connected with railways, and the number of ports connected with road base on the “intermodal and multimodal concept”. On the other hand, the output factors most related to trade and economics are GDP, transport, import, and export volume. The paper applied DEA (Data Envelopment Analysis) model by using DEAP software to analyze the data. The result reveals that the efficiency of infrastructures connectivity and international trade in 10 countries were efficient and 5 countries were inefficient. The research study presents ways of development to improve the connectivity by investing in the basic infrastructures, such as increasing the logistics connection points and driving forward for international trade in the RCEP. Full article

This paper introduces the concept of R4 (road-rail-ro-ro), a concept increasingly used in transport and logistics research circles that defines the modern concept of the transport chain as it passes through the intermodal use of rail, road, and ship via ro-ro. The integration of the new rail-road freight services into the reference supply model allows us to define the supply model for the design scenario on which the evaluation is now focused in terms of service-mode demand shares and in terms of design network flows and performance indicators carried out by demand-supply interaction models applied to all available service-modes. The use of strength-weaknesses-opportunities-threats analysis (SWOT) allows for the identification of some strategies to enhance and improve the current rail and maritime corridors in order to attract more customers using the different services, ultimately triggering the involvement of more actors in generating bigger and better integrated logistic chains using intermodality. The SWOT analysis allows the identification of a series of measures in order to adapt, maintain, enhance or exploit the aspects arising from the expert analysis. Full article