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    <title>Transport Research International Documentation (TRID)</title>
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    <copyright>Copyright © 2026. National Academy of Sciences. All rights reserved.</copyright>
    <docs>http://blogs.law.harvard.edu/tech/rss</docs>
    <managingEditor>tris-trb@nas.edu (Bill McLeod)</managingEditor>
    <webMaster>tris-trb@nas.edu (Bill McLeod)</webMaster>
    <image>
      <title>Transport Research International Documentation (TRID)</title>
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      <link>https://trid.trb.org/</link>
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    <item>
      <title>Carbon reduction and peaking pathway evaluation of container intermodal network: From the perspective of policy sentiment</title>
      <link>https://trid.trb.org/View/2569174</link>
      <description><![CDATA[Carbon peaking and carbon neutrality represent the ambitious commitments of humans to harmonise society and nature. Achieving carbon peaking in intermodal network requires attention to the coordinated development of economic benefits and carbon reduction as well as the collaboration of network elements in dynamic environments based on current policies. Thus, this study proposes an intermodal network carbon-reduction improvement methodology based on policy sentiment analysis, incorporating a machine learning-based sentiment analysis of carbon-reduction policies into the multi-objective optimisation framework. Scenario parameters are integrated into model constraints to generate network transport mode choices and path allocation schemes for various scenarios. In this way, this study evaluates the impacts of policy sentiment, network connectivity, and energy structure on network carbon-reduction improvement and carbon peaking performance. Through the case study of the Yangtze River Delta’s intermodal network, the results reveal that shifting transport modes based on carbon peak targets involves more than the low-emission transport modes replacing high-emission ones. Various transport modes are constantly optimised and adjusted to achieve the optimal compatibility ratio with the changing network structure and advancements in energy technology. From the government’s carbon-reduction sentiment perspective, appropriately tightening carbon policies can improve the quality of carbon peak, achieving it sooner and at a lower level. However, overly strict policies may not offer substantial benefits in terms of effectiveness. The findings provide a theoretical framework to guide government decision-making in reducing transportation carbon emissions.]]></description>
      <pubDate>Tue, 15 Jul 2025 09:47:42 GMT</pubDate>
      <guid>https://trid.trb.org/View/2569174</guid>
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    <item>
      <title>Less-than-container cargo scheduling for China Railway Express along belt and road initiative routes</title>
      <link>https://trid.trb.org/View/2522386</link>
      <description><![CDATA[With the rapid expansion of global trade, the use of LCL(Less than container load) transportation in international trade is becoming increasingly widespread. This study explores the application of LCL transportation in the context of China Railway Express (CR Express). Addressing the challenges of low cargo loading efficiency and complex container scheduling in CR Express LCL services, the authors aim to maximize customer satisfaction and develop a multi-objective mixed-integer programming model. The model aims to minimize the number of containers used and the maximum transportation time. To effectively tackle large-scale instances, they have designed an efficient genetic algorithm enhanced with an iterative local search (ILS-GA). Computational experiments across small, medium, and large instances reveal that ILS-GA identifies optimal solutions in small-scale instances. ILS-GA discovers the optimal solution within an average runtime of 5.45 s, which is 95.56% faster than CPLEX’s 180 s, demonstrating its high solution efficiency. In medium and large instances, compared to CPLEX and SA, ILS-GA provides better solutions with higher computational efficiency, significantly outperforming the SA algorithm in terms of global search capability and optimization efficiency. Additionally, they analyze the initialization and local iterative search strategies through experiments, verifying the proposed strategies’ effectiveness in improving the ILS-GA solutions.]]></description>
      <pubDate>Fri, 28 Mar 2025 09:12:06 GMT</pubDate>
      <guid>https://trid.trb.org/View/2522386</guid>
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    <item>
      <title>They do it with containers: examining fatalities of transnational human smuggling and evaluating the modus operandi via multimodal transportation</title>
      <link>https://trid.trb.org/View/2475262</link>
      <description><![CDATA[This paper examines global patterns of Transnational Human Smuggling through container boxes. The dataset compiled for this study analyzes known global cases of fatal incidents in containers from 2000 to 2024, with a total of 1,824 smuggled persons found either (a) dead, (b) unhealthy/injured, or (c) alive and relatively healthy. 3. It provides a comprehensive study on how smugglers obtain lucrative fees for transporting persons on perilous, often deadly voyages. An originally compiled dataset demonstrates the primary global smuggling routes while addressing (i) the type of containers that smugglers use over time, (ii) the transport mode (i.e., land and sea), (iii) the ethnicity of smugglers vs. smuggled persons, (iv) statistics of persons found alive, sick, injured, or dead, and (v) death causes of smuggled groups. While human smuggling in maritime containers represents a small percentage of the illegitimate flows at U.S. borders, its significance cannot be overstated as it poses increased health and safety risks to travelers. This paper highlights the critical smuggling-related security vulnerabilities of sea and land containerized commerce. Furthermore, this study focuses on persons smuggled in containers, hence excluding undocumented migrants entering national borders on foot. Smugglers use various modes of transportation to move people illegally, but the use of containers is particularly noteworthy. Containers are secured from the outside and transported through highly monitored hubs. Unfortunately, the smuggled individuals cannot open these containers from the inside, making them highly susceptible to harsh weather conditions or abandonment by smugglers if they are alerted of approaching authorities. In such instances, the smuggled individuals are often left to perish.]]></description>
      <pubDate>Wed, 29 Jan 2025 16:56:42 GMT</pubDate>
      <guid>https://trid.trb.org/View/2475262</guid>
    </item>
    <item>
      <title>Improving empty container management using street-turn: A case study of the Colombian logistics network</title>
      <link>https://trid.trb.org/View/2256404</link>
      <description><![CDATA[This case study addresses the problem of empty container repositioning (ECR) in the Colombian context at a regional scale. The research was motivated by the massive empty container congestion in 2022 in specific nodes of the logistics network. A Mixed methods approach is proposed in this research applying qualitative and quantitative methods that aim to clarify the causes of inefficiency in empty repositioning and to formulate improvement strategies. Street-turn has proven to be a strategy to increase the efficiency in the ECR system. A matching algorithm is developed to pair empty containers in inland destinations with export loads, to achieve a more efficient utilization of trucks in the network. Despite the significant container trade imbalance, the optimization model results confirm significant cost savings and reduction of empty trips of up to 50% for RFT between Colombia's two main ports and their principal hinterland regions. The research also identifies that the actors involved in the ECR system lack incentives to deepen their collaboration, which represents a significant barrier to the implementation of street-turn.]]></description>
      <pubDate>Tue, 17 Oct 2023 13:42:33 GMT</pubDate>
      <guid>https://trid.trb.org/View/2256404</guid>
    </item>
    <item>
      <title>Efficiency of Routes in Middle Eastern Transport Corridor</title>
      <link>https://trid.trb.org/View/1975384</link>
      <description><![CDATA[The article presents the calculations for comparison and the choice of the most effective route in the organization of international transport. The southern and northern routes on the railways of the Republic of Kazakhstan are presented when cotton is transported in 20-foot containers from China to the station of the same name and the port of Bandar-Abbas of the Islamic Republic of Iran.]]></description>
      <pubDate>Thu, 23 Feb 2023 09:31:12 GMT</pubDate>
      <guid>https://trid.trb.org/View/1975384</guid>
    </item>
    <item>
      <title>Forecasting worldwide empty container availability with machine learning techniques</title>
      <link>https://trid.trb.org/View/2000116</link>
      <description><![CDATA[Due to imbalances in the global transport of containerised goods, liner shipping companies go to great lengths to match the regional supply and demand for empty containers by transporting equipment from surplus to deficit regions. Making accurate forecasts of regional empty container availability could support liner companies and other involved actors by making better relocation decisions, thus avoiding unnecessary transport costs of empty equipment. Previously proposed container availability prediction models are limited to the application in individual regions and typically characterized by a high degree of temporal aggregation. Against this background, this paper introduces two novel approaches based on machine learning and probabilistic techniques to predict the future weekly availability of empty containers for more than 280 locations worldwide. The machine learning and probabilistic prediction models are built by analysing a unique data set of more than 100 million events from past container journeys. These events represent different stages during the transport process of a container. Both models use a two-step forecast logic. First, the expected future location of a container is predicted. Second, the expected timestamp for arriving at that location is estimated. The machine learning model uses artificial neural networks and mixture density networks to forecast the movements of containers. The models are quantitatively assessed and compared to the actual availability of containers and two more conventional forecasting approaches. The results indicate that the probabilistic prediction approach can keep up with conventional approaches while the neural network approach significantly outperforms the other approaches concerning every evaluation metric.]]></description>
      <pubDate>Thu, 15 Sep 2022 09:20:47 GMT</pubDate>
      <guid>https://trid.trb.org/View/2000116</guid>
    </item>
    <item>
      <title>An innovative intermodal solution to urban residential waste disposal in large cities: a marine highway solution to a growing environmental problem</title>
      <link>https://trid.trb.org/View/1930194</link>
      <description><![CDATA[Large cities face growing challenges of waste disposal due to the increase in urban population, economic development, and goods consumption, resulting in congestion, noise, and air pollution. The traditional trucking of waste material from collection points to landfills or garbage incinerators is no longer viable due to shrinking landfill capacity, stringent environmental regulations, and scarcity of land in urban areas. Recognizing all of these, New York City (NYC) initiated the first marine highway request for proposals (RFP) in the USA calling for a new waterborne proposal to export its residential waste material out of the region. An energy-from-waste (EFW) leading firm, seizing the opportunity, contracted the authors to develop an intermodal system. The authors developed a multimodal transportation system for the EFW firm and NYC that could eventually become a model and a solution to the mounting problems of urban waste management around the world for cities on the waterfront. The authors' approach consists in shipping the waste material to a power plant out of the city that generates energy from waste, with guarantees of state-of-the-art pollution control technologies. This poses transport challenges. The authors used a supply chain approach to illustrate the viability of a large-scale container intermodal system (truck–water–rail) via waterways and marine terminal facilities. This approach is built on containerized equipment, watertight container compartments, and intramodality. The authors used statistical analysis of daily waste volumes applied to standard weekly waste amounts and holiday peaks to determine the demand for tugs, barges, railcars, and containers, including a degree of redundancy. This paper presents the analysis results, from modeling and simulating to the system implementation that was used by the EFW firm to become the first waste disposal waterborne operating system in NYC and a model to emulate elsewhere. The operation, now fully implemented, reduces the number of truck miles driven, wear-and-tear on the roads and trucks, fuel consumption, congestion, noise, and pollution. The paper demonstrates that intermodal solutions are viable for large-scale waste disposal in major urban areas, utilizing existing waterways. A marine highway system is critical to solve goods movement problems and the growing challenges for urban freight movement and waste disposal.]]></description>
      <pubDate>Thu, 26 May 2022 09:11:34 GMT</pubDate>
      <guid>https://trid.trb.org/View/1930194</guid>
    </item>
    <item>
      <title>Task-Container Matching Game for Computation Offloading in Vehicular Edge Computing and Networks</title>
      <link>https://trid.trb.org/View/1883089</link>
      <description><![CDATA[Parked Vehicle (PV) assistance in vehicular edge computing and networks is proposed to exploit underutilized computing resources from PVs for enhancing the resource capacity at the edge vehicular network. Containerization is used to improve task execution of PVs with fast start-up time, less hardware overheads and safe resource isolation. To this end, the authors introduce a task-container matching market to provide on-demand offloading services. For network implementation, the related entities including requesters, PVs with containers as performers and a service provider are described. Considering parking behaviors and resource availability, the authors measure the serviceabilities of PVs to select appropriate PVs for reliable and efficient task processing. According to utility functions, preference profiles of requesters and performers in the task-container matching market are modeled through the best response analysis. Finally, the authors apply matching game approach to cope with associations between tasks and containers deployed inside PVs. Numerical results demonstrate that compared with baseline schemes, the scheme accomplishes more tasks and acquires a higher overall utility in computation offloading.]]></description>
      <pubDate>Thu, 21 Oct 2021 11:12:34 GMT</pubDate>
      <guid>https://trid.trb.org/View/1883089</guid>
    </item>
    <item>
      <title>Multi-Period Inland Depot for Empty Container Expansion Problem</title>
      <link>https://trid.trb.org/View/1572582</link>
      <description><![CDATA[The trade imbalance in the U.S. where there is a greater percentage of imports than exports require a constant repositioning of empty containers. These regional movements create unproductive and unnecessary empty truck tips that contribute to highway congestion, traffic safety and urban emissions. This paper proposes a mixed-integer programming model for the empty container allocation problem with consideration of existing terminal expansion, level of street turns and multiple periods for decision making. In each period, the objective is to determine the location of new empty container depot(s) and amount of capacity to expand at existing depots with a given budget for the period. The proposed model is tested on a 15-node hypothetical network with different levels of street-turns. Results indicate that when depot owners have sufficient budget to spend and more flexibility in terms of being able to shift their budget between decision making periods, the greater the percentage of empty vehicle miles they can reduce at the regional level. Establishing new container depots are found unnecessary when there is a higher level of street-turns.]]></description>
      <pubDate>Fri, 01 Mar 2019 15:51:03 GMT</pubDate>
      <guid>https://trid.trb.org/View/1572582</guid>
    </item>
    <item>
      <title>Evaluating economic and environmental value of liner vessel sharing along the maritime silk road</title>
      <link>https://trid.trb.org/View/1506779</link>
      <description><![CDATA[The Belt and Road initiative is a novel exploration of China towards strategic collaboration with Eurasia countries to an extent of a larger scale with higher and deeper level of cooperation. To meet the growing global demand of transportation, increasing numbers of liner shipping companies collaborate and form alliances to share vessel capacity and reduce capital costs. Effective liner shipping vessel sharing is essential for the Belt and Road initiative in terms of building efficient maritime transport networks. In promoting environmental development, shipping companies are required to attain higher environmental standards. However, limited literature relates vessel sharing to environmental performance. This paper studies the impacts of liner vessel sharing from the economic and environmental perspectives. Two container allocation models are developed for the two scenarios: with and without vessel sharing. The carbon emissions in transportation are calculated under both scenarios. Numerical studies are carried out using services along the China-Indochina Peninsula Economic (CIPE) Corridor. Liner shipping companies could benefit from vessel sharing in terms of significant profit improvement. Vessel sharing could also benefit the environment by reducing the CO₂ emissions dramatically.]]></description>
      <pubDate>Tue, 22 May 2018 11:48:54 GMT</pubDate>
      <guid>https://trid.trb.org/View/1506779</guid>
    </item>
    <item>
      <title>Efficient Solution Methods for the Integer Programming Models of Relocating Empty Containers in the Hinterland Transportation Network</title>
      <link>https://trid.trb.org/View/1488023</link>
      <description><![CDATA[Shintani et al. (2010) developed five integer programming models to analyze the effects of using foldable containers in hinterland transportation. They solved the models using a general purpose integer programming algorithm and mentioned that other powerful solution methods are needed to solve a large size model. In this paper, we develop analytical solutions for two of their models and show that a network flow algorithm solves another two models.]]></description>
      <pubDate>Thu, 30 Nov 2017 09:53:54 GMT</pubDate>
      <guid>https://trid.trb.org/View/1488023</guid>
    </item>
    <item>
      <title>The logistic of empty containers' return in the liner-shipping network</title>
      <link>https://trid.trb.org/View/1482117</link>
      <description><![CDATA[The Maritime Transport is a favoured tool regarding the universal exchanges because it has gone through several evolutions. Indeed, the containerization is considered as one of the most remarkable improvements in the shipping. The containers are rented by shipping companies. However, these companies meet an empty container availability problem at some ports of Maritime Transport Network (MTN) to satisfy the demands of clients. The objective of this work is to solve the problem of the imbalance of the distribution of containers and look for empty containers at less cost to meet the demands of clients. As a result, the authors propose an application to represent the MTN, and provide a balanced distribution of containers. The work presented in this article is based on a heuristic method by neighbourhood. It allows the process of the clients' demands and transfers of full containers as well as the research of empty containers by optimizing the cost of theirs return.]]></description>
      <pubDate>Tue, 28 Nov 2017 09:19:34 GMT</pubDate>
      <guid>https://trid.trb.org/View/1482117</guid>
    </item>
    <item>
      <title>Local container truck routing problem with its operational flexibility</title>
      <link>https://trid.trb.org/View/1439734</link>
      <description><![CDATA[This paper describes a study of the container truck routing problem for pickup and delivery of fully-loaded and empty containers in a local area, considering its operational flexibility. In a container truck operation, an empty container can be transported to a container yard or customer. In addition, since a container can be separated from a truck, two consecutive tasks, a delivery task followed by a pickup task at the same customer can be served by a truck or different truck. Such features of container trucks bring up street turn and decoupling strategy in container truck routing and scheduling. Contrary to pervious studies, this paper considers all pickups and deliveries of containers as independent tasks and two types of consecutive tasks from the perspective of customers incorporating the flexible operation of truck. In a simplified truck routing network, the total operating cost traveled by a truck with an empty container and without a container are minimized. The problem is formulated as an asymmetric multiple- vehicle Traveling Salesman problem with Time Windows (am-TSPTW) including driver’s work-shift hours. A heuristic approach is developed based on an insertion heuristic and a Variable Neighborhood Search (VNS) to solve the problem more efficiently. Result from numerical experiments showed that container truck routes reflecting the two flexibilities reduced the total cost of operation compared with routes without the flexibility. Hence, the proposed problem and solution approach enable a trucking company to accomplish the tasks under two strategies with reduced cost and improved operational efficiency.]]></description>
      <pubDate>Mon, 27 Mar 2017 09:34:04 GMT</pubDate>
      <guid>https://trid.trb.org/View/1439734</guid>
    </item>
    <item>
      <title>A joint optimization model for liner container cargo assignment problem using state-augmented shipping network framework</title>
      <link>https://trid.trb.org/View/1411059</link>
      <description><![CDATA[This paper proposes a state-augmented shipping (SAS) network framework to integrate various activities in liner container shipping chain, including container loading/unloading, transshipment, dwelling at visited ports, in-transit waiting and in-sea transport process. Based on the SAS network framework, the authors develop a chance-constrained optimization model for a joint cargo assignment problem. The model attempts to maximize the carrier’s profit by simultaneously determining optimal ship fleet capacity setting, ship route schedules and cargo allocation scheme. With a few disparities from previous studies, the authors take into account two differentiated container demands: deterministic contracted basis demand received from large manufacturers and uncertain spot demand collected from the spot market. The economies of scale of ship size are incorporated to examine the scaling effect of ship capacity setting in the cargo assignment problem. Meanwhile, the schedule coordination strategy is introduced to measure the in-transit waiting time and resultant storage cost. Through two numerical studies, it is demonstrated that the proposed chance-constrained joint optimization model can characterize the impact of carrier’s risk preference on decisions of the container cargo assignment. Moreover, considering the scaling effect of large ships can alleviate the concern of cargo overload rejection and consequently help carriers make more promising ship deployment schemes.]]></description>
      <pubDate>Wed, 27 Jul 2016 09:49:40 GMT</pubDate>
      <guid>https://trid.trb.org/View/1411059</guid>
    </item>
    <item>
      <title>Minimax Regret Model for Liner Shipping Fleet Deployment with Uncertain Demand</title>
      <link>https://trid.trb.org/View/1393148</link>
      <description><![CDATA[This paper proposes a minimax regret model for liner shipping fleet deployment with uncertain demand. The minimax regret model does not need the probability distribution function of the demand, and the model is consistent with how network planners are evaluated. However, the model is large because of the incorporation of all possible demand scenarios. A dynamic scenario inclusion method is proposed for efficiently solving the minimax model with only a small subset of the demand scenarios. A case study based on an Asia–Europe–Oceania liner shipping network demonstrates the applicability of the proposed model and method.]]></description>
      <pubDate>Mon, 01 Feb 2016 09:27:38 GMT</pubDate>
      <guid>https://trid.trb.org/View/1393148</guid>
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