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Abstract Multimodal transport is a challenging, NP-hard problem in combinational optimization and has been solved using evolutionary algorithms, which excel at solving large-scale problems. However, few studies have used evolutionary algorithms, particularly swarm intelligence algorithms, to concurrently handle multiple multimodal transport instances. Ant colony optimization (ACO), which is a population intelligence technique that is adept at identifying the optimal paths in graphs, has been primarily used to address tasks separately rather than concurrently. Therefore, in this study, we introduce a multipopulation-based multitask environment where task-specific populations run in parallel, and ACO serves as the optimizer for each task. A variance-based population diversity measure is then calculated to characterize the distribution differences among individuals. If the population diversity of a specific task falls below a predetermined threshold, the valuable routing traits extracted from other tasks are transferred to the stagnant population. Our method is called population diversity-controlled multitask ACO (PDMTACO). We use multiple benchmark traveling salesman problem (TSP) instances at different scales to validate the efficacy of PDMTACO. Subsequently, we extend PDMTACO to address a series of multimodal transport problems. Our experimental results demonstrate that the use of information transferred by our method significantly reduces its logistics costs and carbon emissions in all multimodal transport tasks.

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]

To better guide decision-making and cost optimization for LNG (liquefied natural gas) tank container multimodal transport routes, aimed at minimizing transportation costs, a mathematical model for optimizing LNG tank container multimodal transport routes based on transshipment terminals was constructed. The study investigated a three-tier multimodal transport network consisting of LNG receiving terminals, transshipment terminals, and customers. A two-stage approach was employed. The overall transportation route planning problem based on transshipment terminals was addressed in the first stage, while the optimization of multimodal transport modes was dealt with in the second stage, building upon the results of the first stage. The GAMS, CPLEX, and DICOPT solvers were used for instance analysis of models. The results revealed that, compared to the traditional point-to-point direct transportation mode, the combination of transshipment terminals and multimodal transport could significantly reduce transportation costs. Meanwhile, sensitivity analysis on the capacity and discount coefficient of cross docks was conducted in this paper, and it was found that changes in the discount coefficient and capacity would have a direct impact on the selection of transportation modes, transportation routes, and overall transportation costs. The case studies validated the effectiveness and feasibility of the transportation model proposed in this paper. The research showed that adopting the transportation mode proposed in this article was expected to significantly reduce transportation costs and provide valuable reference for LNG supply enterprises. [ABSTRACT FROM AUTHOR]

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]

For reduce the carbon emissions of grain transportation, improve ment the efficiency of grain transportation and ensurance the safety of grain transportation, this paper constructed a location-routing optimization model of grain transshipment hub driven by low carbon according to the perspective of quantitative analysis. An improved genetic algorithm was designed to solve the model, which could improve and optimize the layout of China's existing grain transportation network. Finally, some provincial capital cities on the key line of grain logistics were selected for analysis and verification. The results showed that The model and algorithm of hub node sitting-route optimization in hub-spoke multimodal transport network could reduce the total grain transportation cost by 13.87%. Carbon emissions were reduced by 11.70%, and the average transfer saturation of hubs was increased by 9.66%. This method was suitable for the actual grain transportation process, and can realize the low-carbon and efficient transportation of grain, which could provide reference for the location and path planning of Chinese grain transport hub under low-carbon drive.

The environmental issues within the transport industry need to be given priority attention. Optimizing the transport structure and promoting low-carbon transport are essential measures for achieving carbon emission reduction. However, the rail-water multimodal transport scale is currently limited. The government has to intervene in the market through incentive policies, so how to expand the revenue of carriers and enhance the volume has become a major dilemma. Our paper constructs a transport system that includes road, water, and railway, and examines the impact of incentive policies on separate stakeholders. It is discovered that incentive policies can increase the revenue of carriers and simultaneously attract more shippers to elect rail-water multimodal transport. Subsidy policy can hasten the structural transformation of inland transport, making railway transport volume rise. Unfortunately, although the dry port policy may enhance the revenue of railway carriers, it leads to an apparent decline in the revenue of road-water multimodal transport participants. However, the subsidy policy can create a win-win scenario for multiple carriers while achieving carbon emission reduction, but to the detriment of social welfare. Additionally, the paper compares the interactions between diverse incentive policies and pivotal factors such as transport time. The conclusions of our research serve strategic recommendations for maximizing carriers revenues and provide support for government decision-making. • The impact of incentive policies on the rail-water multimodal transport is inspected. • Subsidy policy can make carriers better off, but may have adverse effects on social welfare. • Subsidy policy expands carrier volume and stimulates transport structure transformation. • Although dry port is conducive to social welfare, it hurts the revenue of carriers. • The dry port is beneficial for achieving long-distance carbon emissions reduction. [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]

This paper focuses on optimizing the green multimodal transportation path under the condition of transit time subjected to random distribution with dynamic changes. The study utilizes the transition matrix of a homogeneous Markov chain and the theory of time-space network to simulate the transit time subjected to random distribution with dynamic changes. A time-space network path optimization model is established and solved using a commercial solver. The solutions are compared under different transit time scenarios and carbon tax rates. It is observed that the reliability of the same solution decreases in a transportation environment with higher randomness. Additionally, new solutions that did not appear in a single situation are generated under dynamic changes in transit time. As the carbon tax rate increases, the transportation strategy gradually shifts away from road transportation. Furthermore, the time-space network model may yield better solutions compared to the physical network model. The choice of different types of distributions to simulate transit times also influences the solution results. [ABSTRACT FROM AUTHOR]

This paper presents a comprehensive modeling framework for large-scale agent-based multimodal transportation simulation tailored to the complex urban environments of megacities, with a specific focus on the Greater Los Angeles (LA) area. The framework leverages the Multi-Agent Transport Simulation (MATSim) toolkit, which addresses the evolving challenges posed by urbanization and technology-driven shifts in human mobility patterns. The framework enables the generation of explicit travel trajectories for a representative 10% sample population of LA County, comprising over one million individuals. To ensure the model's validity, an efficient network calibration algorithm is proposed with rigorous validation using publicly available traffic count data. This paper underscores the development and configuration of the agent-based simulation model for LA, providing a robust foundation for large-scale urban mobility simulations and advancing our understanding of the intricacies of megacities. [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]

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]

Abstract 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.

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]

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]

Copyright of Romanian Review of Private Law / Revista Română de Drept Privat is the property of Universul Juridic Publishing House 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 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 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]

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.

In the process of long-distance and large-volume transportation of hazardous materials (HAZMAT), multimodal trans-portation plays a crucial role with its unique advantages. In order to effectively reduce the transportation risk and improve the reliability of transportation, it is particularly important to choose a suitable transportation plan for multimodal transport of HAZMAT. In this paper, we study the transportation of HAZMAT in multimodal transport networks. Considering the fluctuation in demand for HAZMAT during the actual transportation process, it is difficult for decision makers to obtain the accurate demand for HAZMAT orders in advance, leading to uncertainty in the final transportation plan. Therefore, in this paper, the uncertain demand of HAZMAT is set as a triangular fuzzy random number, and a multi-objective mixed integer linear programming model is established with the objective of minimizing the total risk exposure population and the total cost in the transportation process of HAZMAT. In order to facilitate the solution of the model, we combined the fuzzy random expected value method with the fuzzy random chance constraint method based on credibility measures to reconstruct the uncertain model clearly and equivalently, and designed a non-dominated sorting genetic algorithm (NSGA-) to obtain the Pareto boundary of the multi-objective optimization problem. Finally, we conducted a numerical example experiment to verify the rationality of the model proposed in this paper. The experimental results indicate that uncertain demand can affect the path decision-making of multimodal transportation of HAZMAT. In addition, the confidence level of fuzzy random opportunity constraints will have an impact on the risk and economic objectives of optimizing the multimodal transportation path of HAZMAT. When the confidence level is higher than 0.7, it will lead to a significant increase in transportation risks and costs. Through sensitivity analysis, it can provide useful decision-making references for relevant departments to formulate HAZMAT transportation plans.

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.

Cities, even medium-sized and small ones, have become overwhelmed by traffic and congestion. Innovative solutions are required and recent studies have focused on sustainable approaches. This study aims to develop a multimodal transport model consisting of an urban public transportation (UPT) service combined with an e-scooter sharing service. The main purpose of the model is a comparison between two travel alternatives (car and UPT + e-scooter), calculating their associated levels of utility. The methodology is based on a multinomial logit model, implemented in Matlab software, using results from an online mobility survey (socio-economic characteristics of potential users of e-scooters). The additional aim is related to the assessment of the inhabitants’ availability to shift from car to multimodal service or to simple e-scooter service. The developed micromodel was applied in Iași, a mid-sized city located in the northeast of Romania. Several price strategies were analysed in order to find their influence on users’ mobility behaviour. It turned out that the price for the shared e-scooter is too high at this moment to be used for daily travel. Without a price decrease and public authorities’ involvement in facilitating the multimodality, the e-scooter remains only an entertainment activity.

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.)

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.

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.

Background: Inland dry ports in Ethiopia serve as extended destinations for goods transported by sea, especially under the international multimodal transport system, to fulfil customs formalities. Ethiopia’s multimodal transport law gives carriers lien rights to detain cargo and documents to recover all sums payable under multimodal contracts. However, the country’s customs law gives customs the right to sell abandoned goods by auction and collect duties and taxes before any other payments are made. Objectives: This study critically examines current regulations and practices relating to carriers’ lien rights to recover uncollected charges on goods abandoned at inland dry ports. Method: A qualitative case study design is used to analyse the challenges and provide solutions for multimodal transport operators dealing with abandoned goods at inland terminals. Results: A major reason for abandonment is that the proceeds of sales of abandoned goods are insufficient to pay for taxes and logistics expenses. The Ethiopian Shipping and Logistics Services Enterprise has lost an estimated 1.5 million USD annually from abandoned containers in multimodal transport. Conclusion: Based on the legislation and court of appeal precedents presented in this paper, multimodal transport operators’ uncollected charges should take priority over tax and duties for the proceeds of selling abandoned goods. As Ethiopia is a landlocked country, it needs to resolve this issue to ameliorate its multimodal transport system. Contribution: This paper suggests revising existing regulations and practices relating to unclaimed goods at inland terminals to recoup logistics costs ahead of tax. This will facilitate multimodal transport services’ use of inland terminals as extended destinations of seaports.

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]

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Understanding the limits of freight forwarders' liability helps to predict the scope of indemnification to the customer in case of damage or loss of cargo. The absence of international agreements regulating the limit of the liability limit of freight forwarders makes it difficult for customers to find freight forwarders with the most favorable conditions. A large number of factors, such as the type of forwarding contract, the country of registration of the forwarder, the status of the forwarder, existing international agreements, etc. can significantly affect the degree of liability of the forwarder. In this paper, the legislation regulating forwarding and the activities of the multimodal transport operator will be considered. In addition, the standard conditions of the forwarding contract, the most commonly used in the selected countries, will be analyzed. On the basis of the conducted research, a case study will be presented, which will indicate the practical influence of various factors on the liability limit of the forwarder and the multimodal transport operator.

Tourists, like any other users of transport systems, seek to travel safely from origin to destination, choosing the appropriate route in relation to the speed, comfort, and cost of trip. Therefore, the goal is, from a tourism transport planning perspective, to minimize connections and, wherever necessary, make them as efficient as possible. Multimodal solutions allow passengers to adopt less polluting modes of transport whenever possible, encouraging a more sustainable journey. Digital solutions and integrated planning services offer the potential for sustainable, easy-to-use and efficient multimodal travel. The purpose of this article is to present a novel GIS-type IT solution for assessing the cost of multimodal transport to tourist resorts in Romania. The IT platform considers the movement of tourists to tourist resorts through two networks in the intermodal system, railways and national roads, connected through nodes represented by the railway stations.

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.

This study aims to look at the trend of Light Rail Transit (LRT) mass transportation during the covid-19 pandemic as a lesson for multimodal transportation courses. The type of qualitative research that becomes a research instrument is the researcher himself (the author) who is directly involved in the research. The determination of informants in this study uses purposive techniques where only certain people or parties will be used as research objectives as a source of information, namely Informant I: Head of the Section on the Utilization of Facilities and Infrastructure, Informant II: Officials making committees of public service agencies, Informant III: Managers of Passenger Numbers and Revenues, Informant IV: Train Travel Organizers. The results of the study are expected to be able to measure the level of understanding of cadets in the Multiomoda Transportation course. Through the pre-test as the average basis for cadets' knowledge of the Multimodal Transportation course of 87.00, then an intervention was carried out through education and material training based on the results of a research study of light rail transit (LRT) mass transportation trends before and after the Covid-19 Pandemic and a reassessment was carried out to obtain the average post-test results and the results changed to 91.86. Through the Paired Sample T-Test test, the significance value of the pre-test and post-test can be tested, a significance value of 0.000 is obtained, which means that there is a significant difference between the pre-test and post-test values. Furthermore, it can be seen the Correlation value of 0.525 which shows the strength of the relationship of the 2 variables tested, namely pre-test and post-test.

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]