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As a relatively clean energy source, liquefied natural gas (LNG) is experiencing a growing demand. The uneven global distribution of LNG often compels residents in regions without local sources to import it, underscoring the need to optimize the global LNG transportation network. Therefore, this study formulates a nonlinear mixed-integer programming model for a multimodal transport and storage problem to optimize LNG carrier allocation, LNG storage planning, and LNG transport planning, aiming to minimize the total cost of multimodal transport, minus the rewards offered by ports. In order to facilitate the solving of the model, some linearization methods are used to transform the nonlinear model into a linear model. To assess the efficiency of the linear model, we conduct computational experiments on small-scale instances with five inland cities, medium-scale instances with 15 inland cities, and large-scale instances with 60 inland cities. The results show that all small- and medium-scale instances can be solved to optimality within 427.50 s. Feasible solutions with a maximum gap value of 0.03% for large-scale instances can be obtained within 1 h. In addition, sensitivity analyses are conducted to identify the impacts of the cost of transporting LNG by vehicles, the charter cost of LNG carriers, and the rewards for shipping LNG. In general, higher cost of transporting LNG by vehicles and higher charter cost of LNG carriers lead to a higher objective value. It is also found that when the rewards for shipping LNG increase to a certain extent, such that the additional rewards exceed the additional multimodal transport cost incurred, the amount of LNG unloaded at the subsidized port increases. [ABSTRACT FROM AUTHOR]

Copyright of Science Technology & Engineering is the property of Chinese Society of Technology Economics and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

With the growth of cars and car-sharing applications, commuters in many cities, particularly developing countries, are shifting away from public transport. These shifts have affected two key stakeholders: transit operators and first- and last-mile (FLM) services. Although most cities continue to invest heavily in bus and metro projects to make public transit attractive, ridership in these systems has often failed to reach targeted levels. FLM service providers also experience lower demand and revenues in the wake of shifts to other means of transport. Effective FLM options are required to prevent this phenomenon and make public transport attractive for commuters. One possible solution is to forge partnerships between public transport and FLM providers that offer competitive joint mobility options. Such solutions require prudent allocation of supply and optimised strategies for FLM operations and ride-sharing. To this end, we build an agent- and event-based simulation model which captures interactions between passengers and FLM services using statecharts, vehicle routing models, and other trip matching rules. An optimisation model for allocating FLM vehicles at different transit stations is proposed to reduce unserved requests. Using real-world metro transit demand data from Bengaluru, India, the effectiveness of our approach in improving FLM connectivity and quantifying the benefits of sharing trips is demonstrated. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Railway Science & Engineering is the property of Journal of Railway Science & Engineering Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Multimodal transport document collaboration is the foundation of multimodal transport operations. Blockchain technology can effectively address issues such as a lack of trust and difficulties in information sharing in current multimodal transport document collaboration. However, in current research on blockchain-based electronic documents, the bottleneck lies in the collaboration aspect of multimodal transport among multiple entities, known as the "one-bill coverage system" collaborative problem. The collaboration problem studied in this paper involves selecting suitable transport routes according to the shipper's transport needs, and selecting the most suitable specific carrier from numerous carriers. To address the collaboration problem among multiple parties in the multimodal transport "one-bill coverage system", a multiparty collaboration mechanism is designed. This mechanism includes two aspects: firstly, designing the architecture of the multimodal transport blockchain transport platform, which reengineers the operation process of the "one-bill coverage system" for container multimodal transport; secondly, constructing a multiparty collaboration decision-making model for the "one-bill coverage system" in multimodal transport. The model is solved and analyzed, and the collaboration strategy obtained is embedded in the application layer of the platform. Smart contracts related to the "one-bill coverage system" for multimodal transport are written in the Solidity language and deployed and executed on the Remix platform. The design of this mechanism can effectively improve the collaboration efficiency of participants in the "one-bill coverage system" for multimodal transport. [ABSTRACT FROM AUTHOR]

Copyright of Science & Technology of Cereals, Oils & Foods is the property of Science & Technology of Cereals, Oils & Foods Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Due to the trade imbalance and poor management, a large number of empty containers are piled up after unpacking in importing regions, while the export-oriented areas are in urgent need of empty containers for replenishment. This paper aims to determine the volume of empty containers transferred from the surplus area to the shortage area and the inventory of each node from the operational level. We subdivide container freight stations into rail stations and road stations and consider using sea, road, and railway as transportation modes to transfer empty containers. A multi-period linear programing model of multimodal empty container repositioning is established aiming at minimizing the cost of empty container repositioning. A real case study of the transportation network in Northeast China is conducted to demonstrate that using multiple modes of transportation can significantly reduce the cost of empty container repositioning compared to using a single mode of transportation. [ABSTRACT FROM AUTHOR]

To reduce the time value loss of high-value time-sensitive goods and rationalize multimodal transport paths, the influence of the time value of goods on multimodal transport path selection was investigated under uncertain transport demand. Based on the consideration of the value characteristics of the goods, a robust optimization model for multimodal transport paths was established by using the scenario analysis method in the robust optimization method with the objective of minimizing the combined transport cost, time value cost of goods and cost of carbon emission, and the constraints of hard time windows for nodal operations. According to the characteristics of the research problem, a Monte Carlo-based disaster adaptive genetic algorithm was adopted to discuss the model, and a combined transport network consisting of 15 urban nodes and three modes of transport - road, rail and waterway wee used as an arithmetic network for analysis. The results show that the rail distance as a percentage of the total transport distance increases by 17.28% for transport paths taking into account the time value of goods compared to those that do not, resulting in a 12-hour reduction in total transport time and a 16.19% saving in the time value cost of goods. As the average daily decay rate increasing, different transport paths will be chosen in different decay rate ranges. The increasing proportion of rail or road transport distance will be selected to improve transport timeliness and avoid the cost of the time value of goods rising too fast. The uncertainty of demand has increased transport cost, the cost of the time value of goods and the cost of carbon emission by 16.53%, 3.44% and 17.31% respectively. Ultimately it can lead to a 9.65% increase in total transport costs. The results of the study can help decision makers estimate the demand and decay rate based on the actual demand situation and the nature of the goods, and provide a reference for their rational choice of transport paths to avoid excessive loss of time value of the goods. [ABSTRACT FROM AUTHOR]

Cross-border e-commerce logistics activities increasingly use multimodal transportation modes. In this transportation mode, the use of high-performance optimizers to provide decision support for multimodal transportation for cross-border e-commerce needs to be given attention. This study constructs a logistics distribution optimization model for cross-border e-commerce multimodal transportation. The mathematical model aims to minimize distribution costs, minimize carbon emissions during the distribution process, and maximize customer satisfaction as objective functions. It also considers constraints from multiple dimensions, such as cargo aircraft and vehicle load limitations. Meanwhile, corresponding improvement strategies were designed based on the Sand Cat Swarm Optimization (SCSO) algorithm. An improved swarm intelligence algorithm was proposed to develop an optimizer based on the improved swarm intelligence algorithm for model solving. The effectiveness of the proposed mathematical model and improved swarm intelligence algorithm was verified through a real-world case of cross-border e-commerce logistics transportation. The results indicate that using the proposed solution in this study, the cost of delivery and carbon emissions can be reduced, while customer satisfaction can be improved. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Computer Engineering & Applications is the property of Beijing Journal of Computer Engineering & Applications Journal Co Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In the rapidly evolving global marketplace, the logistics sector faces a multitude of challenges that demand implementation of more resilient solutions to respond to any future disturbance. Synchromodal transport, which is viewed as an extension of multimodal transport, is known as a key answer to this issue, as it provides more flexible and sustainable freight transport and also focuses on collaboration between different logistics players. We consider synchromodal transport as a collection of agents that not only have their own characteristics and behaviors, but also interact with each other, which impacts the entire system. In this paper, we study the system using an Agent-Based Modeling approach. The network represents the combination of long-haul and drayage transport, where pre-haulage and end-haulage are done only by truck, and the rest can be done by trucks, trains, or barges. A numerical experiment is conducted to evaluate cost savings and emissions reduction under different logistics service providers' relation and re-routing scenarios. Our findings show that synchromodal scenarios are more economically and environmentally efficient, and that they lead to higher flexibility and reliability compared to business-as-usual scenarios. Additionally, our model verifies that the cost saving is considerable when logistics service providers collaborate with each other. The results of sensitivity analyses show consistent overall trends when comparing the different scenarios. Therefore, the conclusions drawn from the original experiment appear to be applicable, not only for that specific instance, but have broader relevance and applicability. [ABSTRACT FROM AUTHOR]

Copyright of Revista de Derecho Fiscal is the property of Revista de Derecho Fiscal and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Railway Construction Technology is the property of Railway Construction Technology Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The possibilities of joint utilization of future high-speed railways in Ukraine's transportation system, both for passenger and specific freight categories, are examined. An economic-mathematical model of the rational ratio of passenger and freight transportation on one line and the location of stations on it was used for the technological and economic justification of the business model. The model is based on taking into account the costs of construction and operation of the railway, the fee for using the railway infrastructure, the maximum and average operational speed of trains, other operational variables and taking into account the subsidization of unprofitable passenger transport. A methodology for justifying the rational ratio of passenger and freight trains on the lines is proposed, along with the determination of technological and economic parameters for the operation of high-speed railways within Ukraine's multimodal transportation system. An economic-mathematical model is described, which allows for the optimization of design and technological decisions during the construction and operation of high-speed railways, depending on the economic and other conditions of their operation. The parameters of the business model, including indicators of technology and economy of passenger and cargo transportation, were determined. These parameters are used to analyze the technological aspects of the business model, such as the optimal distance between stations, the required number of trains (wagons/containers in trains) for passenger and freight transportation. This allows you to calculate transport costs and the price of transport services to achieve a balance of interests of infrastructure operators and transport operators. On the basis of the obtained results, it is possible to analyze and simulate various scenarios for the development of highspeed railway infrastructure, as well as to determine the market strategy of the infrastructure operator. [ABSTRACT FROM AUTHOR]

This study is a review of the existing literature on the topic of bike-transit combination. The aim is two-fold: (i) to identify factors that influence its successful uptake, and (ii) to discuss the potential of the bike-transit combination and its impact on urban transport systems. The review showed that the bike-transit integration is complex and can be influenced by a variety of factors. These factors are mainly related to the quality of public transport, the cycling network and the integration of these two. Improving them can have a positive impact on bike-transit uptake. Land use and built environment characteristics also play an important role, suggesting that the local context plays a significant role on its successful uptake. In general, the review reveals that bike-transit has shown potential in improving the performance of existing public transport systems, by expanding catchment areas and improving accessibility, but its impacts on car use have not been explicitly studied. The review concludes that the bike-transit combination shows a promising path to sustainable urban mobility and is a topic worth further investigation. However, it also calls for more integrated research approaches and an explicit focus on which types of travel behaviour are substituted by the bike-transit combination. [ABSTRACT FROM AUTHOR]

This article introduces the cumulative school bus routing problem, which concerns the transport of students from a school using a fleet of identical buses. The objective of the problem is to select a drop‐off point for each student among potential locations within a certain walking distance and to generate routes such that the sum of arrival times of all students from their school to their homes is minimized. The article describes six polynomial‐size mixed integer linear programming formulations based on original and auxiliary graphs, and the formulations are numerically compared on real instances. The article reports the results of computational experiments performed to evaluate the performance of the proposed models. [ABSTRACT FROM AUTHOR]

The rationality of profit distribution affects the stability of the multimodal transport alliance. In the multimodal transport alliance, the participation rate of the carrier and the communication structure of the alliance are important influencing factors of profit distribution results. To get a reasonable profit distribution scheme, this paper constructs a profit distribution model considering the characteristics of multimodal transport, called the Choquet Cloud Gravity Center AT model. Firstly, considering the communication structure of the alliance, the Cloud Gravity Center Average Tree method is used as the base model for profit distribution. Secondly, considering the multimodal transport alliance is a fuzzy coalition, the profit for each alliance subset in the base model is calculated by the Choquet integral. Then, the profit distribution model considering participation rate and communication structure is obtained. Finally, a numerical example is given to illustrate the applicability of the model, and comparative analysis is conducted to verify the rationality of the model. This study provides a suitable profit-sharing model for multimodal transport alliances, which is conducive to the stable and efficient operation of alliances. [ABSTRACT FROM AUTHOR]

Using Unmanned Aerial Vehicles (UAVs), commonly referred to as "drones", as a supplementary mode for last-mile deliveries has been a research focus for some years now. Motivation lies in the reduced dependency on Conventional Vehicles (CVs) and fossil fuels and in serving remote areas and underprivileged populations. We are building a flexible, modular framework for integrated CV-UAV parcel delivery operations planning that is responsive to infrastructure and demand and offers an open and practical tool for future adaptations. The entire model and solution methodology are practical tools for decision making and strategic planning, with novelties such as the variable Launch Site types for Launch and Recovery Operations (LAROs), the tailored Assignment and Routing Optimization nested GA, the consideration of airspace restrictions of any shape and size, the inclusion of GIS tools in the process, the modularity of the platform, and most importantly, the inclusion of all the above in a single, comprehensive, and holistic approach. Because of the need for safe UAV deployment sites and the high presence of restricted airspace zones in urban environments, the intended field of application is assumed to be the delivery of small packages in rural and under-connected areas, the execution of inter-city deliveries, and the expansion of a city's original service range. A single CV is equipped onboard with UAVs, while special locations, such as Remote Depots (RDs) with UAVs and Virtual Hubs (VHs) for UAV deployment facilitation, are introduced. The framework considers the presence of Restricted Zones (RZs) for UAV flights. Part of the methodology is implemented in a GIS environment, taking advantage of modern tools for spatial analysis and optimal path planning. We have designed a tailored nested GA method for solving the occurring mode assignment and vehicle routing optimization problems and have implemented our workflow on a devised case study with benchmark characteristics. Our model responds well to unfavorable network types and demand locations, while the presence of RZs notably affects the expected solution and should be considered in the decision-making process. [ABSTRACT FROM AUTHOR]

Copyright of Food Science & Technology & Economy is the property of Grain Science & Technology & Economy Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Purpose: Process of building and then implementation of integrated multimodal, passenger-centred and predominantly sustainable transport system will require a specific effort to be input in preparation, especially if it covers new entrants like passenger Urban Air Mobility. This paper aims to address the first step which is the identification of barriers to be overcome to turn the concept into reality. Design/methodology/approach: Comparison of the current state-of-the-art in transportation, Information and Communication Technologies as well as other city planning domains to the forecasted ecosystem, described in the form of scenarios where base for definition of necessary actions, challenges as well as potential barriers and obstacles were identified and thoroughly specified. Findings: Barriers grouped in five categories: policy, digitalisation, transportation technologies, integration technologies and passengers' needs allow for formulation of the relevant roadmaps defining optimal development path towards fully integrated multimodal, passenger-centred and sustainable transport system. Research limitations/implications: Conclusions can be a starting point in studies towards development of roadmap for implementation of truly integrated municipal transport system both sharing the resources as well as high-level objectives. Practical implications: Conclusions can be exploited in various areas starting from preparation of strategies in cities aspirating to be smart, through definition of technology development priorities by relevant agencies ending with industry actors looking for better trimming their business. Originality/value: The identified barriers as derived from detailed investigation enable deep insight into the total transport system vision in which Urban Air Mobility integrated within urban mobility ecosystem is considered as game-changing factor having large potential to contribute to both making cities smart and sustainable. [ABSTRACT FROM AUTHOR]

Aiming at the problem of multimodal transport path planning under uncertain environments, this paper establishes a multi-objective fuzzy nonlinear programming model considering mixed-time window constraints by taking cost, time, and carbon emission as optimization objectives. To solve the model, the model is de-fuzzified by the fuzzy expectation value method and fuzzy chance-constrained planning method. Combining the game theory method with the weighted sum method, a cooperative game theory-based multi-objective optimization method is proposed. Finally, the effectiveness of the algorithm is verified in a real intermodal network. The experimental results show that the proposed method can effectively improve the performance of the weighted sum method and obtain the optimal multimodal transport path that satisfies the time window requirement, and the path optimization results are better than MOPSO and NSGA-II, effectively reducing transportation costs and carbon emissions. Meanwhile, the influence of uncertainty factors on the multimodal transport route planning results is analyzed. The results show that the uncertain factors will significantly increase the transportation cost and carbon emissions and affect the choice of route and transportation mode. Considering uncertainty factors can increase the reliability of route planning results and provide a more robust and effective solution for multimodal transportation. [ABSTRACT FROM AUTHOR]

Copyright of Rolling Stock (1002-7602) is the property of Rolling Stock Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In a realistic environment, operational decision problems involve several sources of uncertainty, due to measurement errors, approximate parameters, or simply the unavailability of information at the time of decision-making. These disturbances are important in the optimization process and must be taken into consideration. To meet these needs, optimization under uncertainty has emerged as an important area of modern operations research and has gained increasing popularity in recent years by tackling complex optimization problems, such as multimodal chain management and container terminals management. In this regard, the present article provides a general overview of the different optimization paradigms and approaches used in the literature to support decision-making in the face of uncertainty. In particular, this article aims to present a state of the art on application of optimization under uncertainty in multimodal transport problems, with a particular focus on the application of Robust Optimization. [ABSTRACT FROM AUTHOR]

This study examines the potential for reduced risks in roundwood transport by rail. The study quantifies seasonal variation and system risks under boreal conditions, as well as practical routines for managerial response to these. The study case is based on an integrated forest company with 11 supply terminals supplying coastal mills in mid-Sweden. The terminals were distributed from south to north Sweden, with six core terminals located in the interior- and mid-supply zones for coastal mills. The monthly flows ranged from 75 to 118% of the annual average and the monthly variability of terminal inflows was 67% higher for the interior than the mid-zone terminals. Comparing inflows between assortments, the lowest variability was for coniferous pulpwood (8%) and pine sawlogs (18%), increasing thereafter to deciduous pulpwood (28%) and spruce sawlogs (53%). Regarding rail system disturbances, the frequency of deviations from scheduled routes for the core terminals was 16–17%, resulting in canceled routes for 53–65% of deviations. Two mitigation scenarios were tested to reduce supply risks (scenario 1) and a combination of supply and system risks (scenario 2). These risk mitigation scenarios had only marginal effects on system costs (< 1%). The optimal solutions, however, involved a 4–5% reduction of truck transport output (m3km per period) and 7–8% increase in rail output. From the perspective of rail operations, interviews with service buyers and providers showed that the mitigation scenarios were fully feasible on an annual planning horizon. Further options are provided for quarterly, monthly, and weekly horizons. [ABSTRACT FROM AUTHOR]

Multimodal transport has emerged and applied to logistics work as single-mode transport was unable to meet the growing demand for logistics. Due to the difference in cost and time consumption between different modes of transportation, the path planning of multimodal transport is different from that of single-mode transport. This paper firstly established a multimodal railroad consignment path optimization model under the condition of transportation time uncertainty and then optimized the path and transportation mode with the particle swarm optimization (PSO) algorithm according to the path optimization model. In addition, the PSO algorithm was optimized by a genetic algorithm to avoid the optimization process of the PSO algorithm from falling into the locally optimal solution. Finally, simulation experiments were carried out on the improved PSO algorithm, and it was compared with the traditional PSO and genetic algorithms. The results showed that the improved PSO algorithm converged to stability after about 200 iterations, the traditional PSO algorithm converged to stability after about 240 iterations, and the genetic algorithm converged to stability after about 400 iterations; the total transport cost and time of railway transportation were USD 114,300 and 52.5 h; the total transport cost and time of the path obtained by the genetic algorithm were USD 60,400 and 35.6 h; the total transport cost and time of the path obtained by the traditional PSO algorithm were USD 37700 and 24.3 h; the total transport cost and time of the path obtained by the improved PSO algorithm were USD 3,1900 and 23.4 h. [ABSTRACT FROM AUTHOR]

Copyright of Science Technology & Engineering is the property of Chinese Society of Technology Economics and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Sudden infectious diseases and other malignant events cause excessive costs in the supply chain, particularly in the transportation sector. This issue, along with the uncertainty of the development of global epidemics and the frequency of extreme natural disaster events, continues to provoke discussion and reflection. However, transport systems involve interactions between different modes, which are further complicated by the reliable coupling of multiple modes. Therefore, for the vital subsystem of the supply chain-multimodal transport, in this paper, a heuristic algorithm considering node topology and transport characteristics in a multimodal transport network (MTN): the Reliability Oriented Routing Algorithm (RORA), is proposed based on the super-network and improved k-shell (IKS) algorithm. An empirical case based on the Yangtze River Delta region of China demonstrates that RORA enables a 16% reduction in the boundary value for route failure and a reduction of about 60.58% in the route cost increase compared to the typical cost-optimal algorithm, which means that RORA results in a more reliable routing solution. The analysis of network reliability also shows that the IKS values of the nodes are positively correlated with the reliability of the MTN, and nodes with different modes may have different transport reliabilities (highest for highways and lowest for inland waterways). These findings inform a reliability-based scheme and network design for multimodal transportation. [ABSTRACT FROM AUTHOR]

With the increase in carbon emissions from railway transit, green transportation has attracted worldwide attention due to its low pollution and low consumption. In order to improve the transportation efficiency of multimodal transport and reduce carbon emissions, this paper makes a systematic study on the comprehensive optimization model and method of multiple transport tasks and transport modes considering carbon emissions. Firstly, an optimization model is established with transportation distance, transportation time, and carbon emission as transportation objectives. Secondly, an improved fuzzy adaptive genetic algorithm is designed to adaptively select crossover and mutation probabilities to optimize the path and transportation mode by using population variance. Finally, an example is designed, and the method proposed in this paper is compared with the ordinary genetic algorithm and adaptive genetic algorithm, which proves the proposed model and algorithm are effective. In conclusion, it is found that the present multi-objective optimization model based on the improved genetic algorithm can adjust multimodal transport plans and reduce carbon dioxide emissions, which provides a reference basis for logistics enterprises to carry out multimodal transport. [ABSTRACT FROM AUTHOR]

Copyright of Ruch Prawniczy, Ekonomiczny i Socjologiczny (0035-9629) is the property of Adam Mickiewicz University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Rolling Stock (1002-7602) is the property of Rolling Stock Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

To achieve socio-economic and environmental sustainability, utilization of existing capacities and assets has become a key challenge for the transportation sector. This challenge has been recognised by many scholars, policy makers and practitioners leading to a substantial body of new concepts and models. The rather parallel evolution of the Physical Internet (PI) and synchromodal transport presents an opportunity to improve the current unsustainable freight transportation, by inducing a positive modal shift from roads to rails and inland waterways, and improving service levels by better connecting production research with freight movement. This paper thus examines the synchromodal and PI state-of-the-art models together with their designs, methodologies and findings proposed in the scientific literature. The main objective is to assess and explore the correlations between these two concepts in order to understand how they can reinforce each other. Despite the integrated vision of the Alliance for Logistics Innovation through Collaboration in Europe, the findings of this paper yield no well-established interconnections in the scientific literature between PI and synchromodality as they both merely coexist in parallel and address different dimensions, scales and levels of abstraction. This paper thus identifies potential synergies, future research directions and critical questions to be considered by modellers, developers and policy makers. [ABSTRACT FROM AUTHOR]

The increasing demand for multimodal freight transportation makes the expansion of new secondary hubs necessary. The carbon tax has also received attention from various sectors due to the development requirements of green transportation. Therefore, this study proposed a multimodal transport hub location problem, where carbon emissions are specifically considered to achieve green strategic planning. A mixed integer non-linear programming model was formulated to determine the location of newly-built secondary hubs, the distribution of cargo flow and the modes of the transportation links. A tangible adaptive genetic algorithm (AGA) is designed to effectively search for the optimal solution. The result of the secondary hub location based on Ningbo Port shows that the additional secondary hub brought a 41.46% increase in cargo flow, a 2.2% saving in transportation time and a 2.35% saving in total cost. Furthermore, the sensitivity analysis of the carbon tax reveals that a higher carbon tax increases the transport time, and more secondary hubs are needed to reduce the average cargo transport volume and save the total cost. [ABSTRACT FROM AUTHOR]

Efficient transport solutions are based on multimodal systems, with the dominant role of rail and road transport in land versions of the systems and the connecting and directing part of intermodal terminals, transhipment terminals or warehouse centres. The implementation of transport processes is always associated with the risk of lack of timeliness (quality) or threats to people, equipment and cargo (safety) resulting from human, technical, organizational and global factors like pandemics or war. The article contains a risk mapping method in multimodal transport systems configured to estimate the risk of lowering the quality of logistics services (on-time deliveries, etc.). The method combines factors usually considered separately in studies on individual modes of transport. A formal notation of risk factors as a mathematical model was proposed, and a case study was provided to picture the implementation. [ABSTRACT FROM AUTHOR]

With the development of urbanization and the evolution of urban network systems, multimodal urban transport network (MUTN) systems play a vital role in improving network effects and operational efficiency. However, urban transport networks are easily affected by natural disasters and traffic incidents, which can lead to significant human and economic losses. Accordingly, it is vital to be able to assess the resilience of transport networks in the face of various disruptions. This study, therefore, utilizes complex network theory to analyze the resilience of multimodal urban transport networks, with the resilience accessed based on topological indices. The MUTN in Beijing is selected as a case study for simulation analysis. Based on the road network and subway network, a model MUTN is established, and the Monte Carlo method is used to simulate random attacks. The results show that the MUTN in Beijing has good resilience against disruptions. This study guides the evaluation of the overall resilience of multimodal urban transport networks and will be useful for transportation planners and decision-makers in dealing with emergencies and natural disasters in the future. [ABSTRACT FROM AUTHOR]

Copyright of Railway Signalling & Communication Engineering is the property of Railway Signalling & Communication Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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. [ABSTRACT FROM AUTHOR]

It is expected that future transportation technologies will positively impact how passengers travel to their destinations. Europe aims to integrate air transport into the overall multimodal transport network to provide better service to passengers, while reducing travel time and making the network more resilient to disruptions. This study presents an approach that investigates these aspects by developing a simulation platform consisting of different models, allowing us to simulate the complete door-to-door trajectory of passengers. To address the future potential, we devised scenarios considering three time horizons: 2025, 2035, and 2050. The experimental design allowed us to identify potential obstacles for future travel, the impact on the system's resilience, and how the integration of novel technology affects proxy indicators of the level of service, such as travel time or speed. In this paper, we present for the first time an innovative methodology that enables the modelling and simulation of door-to-door travel to investigate the future performance of the transport network. We apply this methodology to the case of a travel trajectory from Germany to Amsterdam considering a regional and a hub airport; it was built considering current information and informed assumptions for future horizons. Results indicate that, with the new technology, the system becomes more resilient and generally performs better, as the mean speed and travel time are improved. Furthermore, they also indicate that the performance could be further improved considering other elements such as algorithmic governance. [ABSTRACT FROM AUTHOR]

Multimodal transportation is a transportation process completed by connecting and transporting two or more vehicles, also known as combined transportation. Road transportation plays a unique role in the operation and development of the logistics industry, and has unique characteristics in many modes of transportation. This article aims to study the optimization of high-speed logistics routes and provide favorable conditions for the development of multimodal transport. In this article, the node time window defined by multi-transmission network scheduling plays a role, and the transmission time is studied. It analyzes at the lowest cost, searches for the best multimodal road route, and provides decision support and route optimization for multimodal transport through two sets of experiments. According to the survey results, more than 80% of expressways have logistics problems, and 60% of expressways have failed to successfully complete transportation operations. By measuring the exchange time of nodes in different modes of transportation and the transportation time between nodes, it can provide effective support for optimizing multimodal transportation routes, effectively promoting the development of the logistics industry and developing the country. Economics and experimental results prove that this procedure is highly applicable. [ABSTRACT FROM AUTHOR]

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Contrasted with the unimodal road mode, multimodal transport is potentially more feasible as it saves cost and lower environmental effect. This paper investigates freight transport and logistics framework to advance sustainable multimodal freight delivery involving road, rail, and waterway in an inland transportation. We consider a genetic algorithm model comprising time, distance, and CO2 emissions. The optimal design system is modeled by adapting Genetic Algorithm (GA) and Matlab (R2016a) software to improve the existing transport split modes with high shipment cost. An optimal model is formulated to integrate the existing modes to mitigate the prevailing economic, social, and environmental issues. A case investigation of 10 regional capitals in Ghana where freights are transported to and from the main national port was useful to formulate and model an optimized sustainable multimodal freight transport and logistics system (SMFTLS). The Matlab software was used to solve containerized cargo shipment in the optimal system and compare it with the previous system. It was realized that the total cost savings achieved from the optimized system was USD 97.03 million (i.e., 4.5%) lower than the same cargo quantity shipped with the existing system. This SMFTLS model will assist governments, policy makers and investors in deciding the appropriate transport schemes that would manage their overall effects. The study recommends the development of rail and waterway infrastructures to help build the resilient sustainable system (SMFTLS) to manage the rising freight transport demands and related economic, social, and environmental issues. [ABSTRACT FROM AUTHOR]

By tradition, transport appraisal relies primarily on travel time savings and monetary values. Assessment tools rarely factor in the perspective of travellers in terms of their subjective travel experience while on the move. Worthwhile travel time introduces the idea that travel can be pleasant, meaningful or worthwhile and not exclusively associated with the economic utility of the activity at the destination of the trip and the work-related productivity during the trip. This paper explores how the "worthwhile use of travel time" can be conceptualised and unpacked, so that it can be adequately captured and integrated into transport appraisal practice. We reviewed the literature on worthwhile travel time and perceived travel experience in psychology, economics, public health and travel behaviour research and we formulated the conceptual framework of worthwhile travel time that is grounded on the traveller's perception of three forms of value emerging from existing literature: enjoyment, productivity, and health. Our conceptual framework of worthwhile travel time suggests that experience factors (i.e. travel conditions as experienced by the traveller) can enable travel activities (i.e. the trip itself or activities on-the-move), which in turn unlock the values of enjoyment, productivity and fitness that influence the perceived worthwhileness of a trip to a different degree each. Additional (explanatory) factors such as the door-to-door trip characteristics, the traveller's personal characteristics and attitude, and the spatial and temporal conditions can also influence the perceived worthwhileness of a trip. On a policy level, the integration of the worthwhile travel time concept into transport appraisal practice could allow future transport investments to offer a better balance between reduced travel times and improved quality and experience of a trip for the traveller. [ABSTRACT FROM AUTHOR]

The last decade of development in distribution processes has proven the need to broaden their understanding as systems with a specific construction of the composition related to the evolution of market conditions and the growing demand of customers for complex logistics services. This imposes the need to create the necessary conditions for producers of distribution services to use modern knowledge, methods and tools of the distribution, marketing and logistics process for the production of high-quality services to meet the specific demand of the logistics distribution market. The specific role in these processes is to create logistics distribution centers, which by size, characteristics, functions, structures and organization will play a crucial role in the development of complex logistics services. This requires examining the market conditions of these developments, changes in distribution processes and logistics processes, and formulating the specific operational position of logistics distribution processes. Within the work, specific references will be presented for the location of logistics distribution centers in seaports. [ABSTRACT FROM AUTHOR]

As the key member states of the RCEP, China and Thailand will achieve more stable economic cooperation. The further prosperity of the Sino-Thai bilateral trade provides an opportunity for the development of multimodal transport between them. Since selecting a suitable multimodal transport route for the bilateral trade is important, this paper establishes a model based on Analytic Hierarchy Process (AHP) and Zero-One Goal Programming (ZOGP) for evaluating and selecting the multimodal transport route between China and Thailand by taking cost, time and risk as affecting factors into account. A numerical analysis by taking Thailand rubber export to China as an example has been done. The results show that the weight of transportation cost is the largest, followed by the transportation risk. By evaluating the seven typical routes from Songkhla (Thailand) to Qingdao (China), an optimal route is found, which proves the effectiveness and rationality of the modeling, and provides decision basis for decision makers. [ABSTRACT FROM AUTHOR]

Multimodal transport is a critical component in developing the international trade economy, and logistics service providers are a critical component in multimodal transport. However, the recent COVID-19 pandemic has seriously affected the transport system, especially in light of the ongoing rise in transportation costs which has increased firm operating costs. Furthermore, the COVID-19 pandemic has severely influenced the economic sector, resulting in decreased growth. This research aims to determine the priorities of the most important factors for developing and improving multimodal transport compared to pre-COVID-19 and during the COVID-19 outbreak. This research consisted of two stages. The first stage used bibliometric analysis to define multimodal transport dimensions and criteria based on the previous and current literature studies on multimodal transport and used confirmatory factor analysis (CFA) to verify the relationship between factors and multimodal transport. The second stage used the fuzzy best-worst method (FBW) combined benefit, opportunity, cost and risk (BOCR) to prioritize the improvement and development of multimodal transport during the COVID-19 crisis, which considers the perspective of logistics service providers in Thailand. These factors, when identified, would help policymakers design more efficient policies to improve and solve multimodal transport problems mainly caused by strict public health measures during COVID-19. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Computer Engineering & Applications is the property of Beijing Journal of Computer Engineering & Applications Journal Co Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

To compete in the international market, the country with a competitive advantage in the heavy manufacturing industry should increase their logistics efficiency. This paper aims to contribute to the optimisation model for project logistics and proposes the improvement strategy for multimodal transport, especially for project logistics cargo. Mixed-method research consisted of a qualitative study to observe the main criteria for transport analysis and perform a case analysis. In the study case about multimodal transport analysis for exporting 250 units of railway carriages from Indonesia's manufacturer to Chittagong Port, the optimum cost obtained based on a combination of the single -12 multi axle-line trailer and General Cargo Vessel 28000 DWT with the unit cost US$16,700 per carriages and total shipping duration of 142 days. The multimodal strategies are more complex than unimodal transport that involve suppliers, management, logistics function improvement, and lean transport management adoption. [ABSTRACT FROM AUTHOR]

Purpose: The aim of this paper is to offer an overview of the current state of research in a specific field of transport, namely synchromodality. This includes a conceptual discussion of this innovative transport concept to differentiate it from previous concepts as well as the identification of the antecedents, mechanisms and effects of synchromodality. Design/methodology/approach: The paper combines systematic and content analysis-based approaches to literature review to analyse and synthesise a final sample of 88 publications related to synchromodality. Findings: Synchromodality is a transport concept in its infancy which suffers from ambiguous definitions and a lack of theoretical grounding. The paper identifies four mechanisms which differentiate synchromodality from other transport concepts: real-time switching, integrated network planning, horizontal collaboration and mode-free booking. Seven technical and six managerial antecedents for these mechanisms of synchromodality are defined. Research limitations/implications: Existing research on synchromodality is largely focused on technical antecedents (e.g. information and communication technology, sophisticated planning systems). Suggestions for further research include managerial problems such as business models or measures to induce a mental shift and trust. Originality/value: This paper gives a structured overview of the research field of synchromodality and presents existing research from a content-focused perspective. It also indicates opportunities for future research and contributes to a generally accepted understanding of synchromodality. [ABSTRACT FROM AUTHOR]

Supply-chain network design is a complex task because there are many decisions involved, and presently, global networks involve many actors and variables, for example, in the automotive, pharmaceutical, and electronics industries. This research addresses a supply-chain network design problem with four levels: suppliers, factories, warehouses, and customers. The problem considered decides on the number, locations, and capacities of factories and warehouses and the transportation between levels in the supply chain. The problem is modeled as a mixed-integer linear program. The main contribution of this work is the proposal of two matheuristic algorithms to solve the problem. Matheuristics are algorithms that combine exact methods and heuristics, attracting interest in the literature because of their fast execution and high-quality solutions. The matheuristics proposed to select the warehouses and their capacities following heuristic rules. Once the warehouses and their capacities are fixed, the algorithms solve reduced models using commercial optimization software. Medium and large instances were generated based on a procedure described in the literature. A comparison is made between the algorithms and the results obtained, solving the model with a time limit. The algorithms proposed are successful in obtaining better results for the largest instances in shorter execution times. [ABSTRACT FROM AUTHOR]