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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>Unlocking the potential: hybrid blockchain and AI-enabled traceability model development and implementation in the dairy industry – proof-of-concept</title>
      <link>https://trid.trb.org/View/2625932</link>
      <description><![CDATA[Conventional traceability systems without real-time information transmission are susceptible to tampering. In contrast, blockchain and artificial intelligence (AI)-enabled traceability models offer transparency and accountability, given their decentralized nature and immutability. This research conceptualizes and develops a hybrid blockchain and AI-enabled traceability (prototype) model and implements it in the dairy industry. The study includes a collaborative research methodology, including a literature review to analyze the existing traceability solutions, identify data entry points, select model requirements, and deploy smart contracts, decentralized applications (Dapps) and Web3 technologies to develop and validate the proposed model via Testnet. The findings present the user interface developed as a prototype traceability model and its characteristics, such as transparency, decentralized nature, and immutability, followed by practical validation. The post-implementation data analysis highlighted the security, privacy, smart contract validation rules, and comparative insights, as well as the alignment of the theoretical model with practical applications using Web3 technologies. This research contributes to the literature on hybrid blockchain and AI-enabled traceability, highlighting the potential for exploring opportunities in the food industry.]]></description>
      <pubDate>Wed, 24 Jun 2026 11:31:26 GMT</pubDate>
      <guid>https://trid.trb.org/View/2625932</guid>
    </item>
    <item>
      <title>A branch-price-and-cut algorithm for sustainable milk-run vehicle scheduling problem with cross-dimensional integration</title>
      <link>https://trid.trb.org/View/2640972</link>
      <description><![CDATA[In response to environmental deterioration and increasingly stringent regulations, this paper investigates a sustainable milk-run vehicle scheduling problem with cross-dimensional integration (SMVSPCI). The problem extends traditional milk-run models by integrating transportation tasks across bidirectional, temporal, and horizontal dimensions, while jointly considering returnable transport item (RTI) management and quantity decisions over multiple periods. To account for demand uncertainty, a scenario-based stochastic framework is adopted, allowing the model to capture multiple possible demand realizations and their associated probabilities. To effectively solve this complex problem, a tailored branch-price-and-cut (BPC) algorithm is proposed, incorporating innovative strategies such as pseudo-dominance, column combination, and column refinement to enhance computational efficiency. Extensive computational experiments on 270 instances demonstrate that the proposed algorithm efficiently handles medium-scale instances while achieving competitive results for larger cases. Comparative analyses further validate the effectiveness of the proposed strategies in improving solution quality and reducing computational time, providing valuable insights for sustainable logistics planning.]]></description>
      <pubDate>Tue, 17 Feb 2026 13:12:50 GMT</pubDate>
      <guid>https://trid.trb.org/View/2640972</guid>
    </item>
    <item>
      <title>New approach for sustainable and resilient dairy farmer selection under uncertainty</title>
      <link>https://trid.trb.org/View/2479837</link>
      <description><![CDATA[In this paper, the authors propose a hybrid multi-criteria decision-making (MCDM) model under fuzzy environment to select sustainable and resilient suppliers for a real case study of dairy industry in Tunisia. Initially, 12 criteria are applied for categorising of suppliers into four indexes including social, environmental, economic, and resiliency index through literature review and experts' opinions. A fuzzy analytic hierarchy process (FAHP) is proposed to calculate the weight of each criterion, which is used as input in a new fuzzy multi-attribute border approximation area comparison (FMABAC) method for ranking suppliers. The proposed approach may help decision-makers to naturally express their preferences for evaluating supplier selection criteria and to identify the most efficient dairy farmers. Finally, obtained results are discussed by using two sensitivity analysis methods, namely, changing the weights of criteria and comparative analysis with other fuzzy MCDM methods.]]></description>
      <pubDate>Fri, 21 Feb 2025 17:08:06 GMT</pubDate>
      <guid>https://trid.trb.org/View/2479837</guid>
    </item>
    <item>
      <title>Cost optimization in the urban distribution of dairy supply – A case of Sanchi, Bhopal, India</title>
      <link>https://trid.trb.org/View/2458811</link>
      <description><![CDATA[The study focuses on optimizing urban distribution in the dairy industry, specifically at Bhopal Sanchi dairy, to enhance efficiency and minimize costs. It evaluates existing routes, identifies inefficiencies, and proposes new distribution strategies. By implementing these changes, significant improvements are achieved, reducing total distribution costs and dead kilometers while improving vehicle capacity utilization. The study emphasizes the importance of addressing urban distribution challenges to meet increasing milk demand efficiently. It contributes to developing sustainable dairy distribution systems by optimizing costs and minimizing losses. ArcGIS software is utilized for route and fleet optimization analysis. Overall, the research addresses the critical need for efficient urban dairy distribution, particularly in India’s context as a major milk producer.]]></description>
      <pubDate>Mon, 16 Dec 2024 11:59:21 GMT</pubDate>
      <guid>https://trid.trb.org/View/2458811</guid>
    </item>
    <item>
      <title>Analysis of sustainable performance indicators in dairy supply chain using fuzzy-DEMATEL</title>
      <link>https://trid.trb.org/View/2437760</link>
      <description><![CDATA[Sustainability has been always a major issue in businesses over the years, as it integrates the triple bottom line goals of the environment, social, and economic aspects. Dairy is an important sector in many nations since it generates a large number of jobs and economic activity. This article identifies key sustainable performance indicators (SPIs) that may be used as a decision-making variable in the assessment of dairy supply chain performance. The fuzzy decision-making trial and evaluation laboratory (DEMATEL) approaches has been utilised to analyse the SPIs. The total supply chain cost is the most significant SPI, with a weightage of 6.32% which is influenced by all indicators. Profit sharing and stakeholder relationship management are regarded as the least significant SPIs, with a weight of 4.28%. The findings might be used to further understand the SPIs along with sustainability measurement.]]></description>
      <pubDate>Fri, 08 Nov 2024 15:52:34 GMT</pubDate>
      <guid>https://trid.trb.org/View/2437760</guid>
    </item>
    <item>
      <title>Efficacy of Crustacean and Protein-Based Biopolymer Inclusion on the Strength Characteristics of Organic Soil</title>
      <link>https://trid.trb.org/View/2422977</link>
      <description><![CDATA[The current study evaluated the potential of crustacean polysaccharide and protein-based biopolymers, namely, chitosan and casein, in ameliorating a low organic soil. The inclusion of these biopolymers will ensure the reusability and recyclability of waste materials derived from the marine industry and dairy industry, respectively. The unconfined compressive strength and consolidated undrained shear parameters were investigated at varying dosages of chitosan and casein (0.5%, 1%, 2%, and 4%) and curing periods (up to 90 days). The compressive strength increased with an increase in the curing period and dosage and led to maximum values of 4.39 and 3.13 MPa for chitosan- and casein-treated soils, respectively, for 4% dosage and 90 days of curing. The effective cohesion (c′) and friction angle (ϕ′) improved after including chitosan and casein. The scanning electron microscopy images revealed that the filler characteristics of chitosan led to strength improvement up to 60 days and developed bond strength via fiber bridging after 60 days of curing at higher dosages. In contrast, the casein–soil mix revealed a higher fibrous structure after a curing period of 28 days, which resulted in strength improvement. This contributed to the highest effective friction angle of 21.57° for the 2% and 60-day-cured casein–soil mix. Casein outperformed chitosan in imparting higher effective shear parameters at 1% and 2% dosages. Fourier transform infrared analysis validated the absence of any new compounds within the soil structure. The research findings on chitosan and casein from the current study recommend the application of these materials for addressing the issues of unstable slopes and pavement subgrade.]]></description>
      <pubDate>Tue, 15 Oct 2024 09:17:54 GMT</pubDate>
      <guid>https://trid.trb.org/View/2422977</guid>
    </item>
    <item>
      <title>Sustainable Pricing-Production-Workforce-Routing Problem for Perishable Products by Considering Demand Uncertainty; A Case Study from the Dairy Industry</title>
      <link>https://trid.trb.org/View/1933216</link>
      <description><![CDATA[The production routing problem seeks to simultaneously optimize production, routing, and inventory decisions for the plant and the suppliers. In this article an integrated multi-objective sustainable pricing-production-workforce-routing problem is presented for perishable products. Total profit, workforce planning, and vehicle fuel consumption are considered as objective functions due to the importance of operational performance, social, and environmental concerns. The application of the proposed approach is investigated using real case data from a dairy product supply chain. Furthermore, a new solution approach, called Fuzzy Domination Self-Learning Non-Dominated Sorting Algorithm (FDSL-NSGA-II), is developed to solve the problem. The results show that the Pareto solutions of FDSL-NSGA-II outperform those of the classic NSGA-II. Moreover, the findings show that the proposed model can create a surpassing tradeoff between the various aspects of a supply chain, including production, distribution, and workforce planning. In addition, it concurrently optimizes the selling price and protects the environment from the negative impacts of greenhouse gas emissions (GHGs). A comprehensive analysis of the results reveals several managerial insights for decision makers in the logistics industry.]]></description>
      <pubDate>Tue, 12 Apr 2022 10:05:21 GMT</pubDate>
      <guid>https://trid.trb.org/View/1933216</guid>
    </item>
    <item>
      <title>Biofuel recovery from microalgae biomass grown in dairy wastewater treated with activated sludge: The next step in sustainable production</title>
      <link>https://trid.trb.org/View/1922175</link>
      <description><![CDATA[Microalgae biofuel could be the next step in avoiding the excessive use of fossil fuels and reducing negative impacts on the environment. In the present study, two species of microalgae (Scenedesmus obliquus and Chlorella vulgaris) were used for biomass production, grown in dairy wastewater treated by activated sludge systems. The photobioreactors were operated in batch and in continuous mode. The dry biomass produced was in the range of 2.30 to 3.10 g L⁻¹. The highest volumetric yields for lipids and carbohydrates were 0.068 and 0.114 g L⁻¹ day⁻¹. Maximum CO₂ biofixation (750 mg L−1 day−1) was obtained in continuous mode. The maximum values for lipids (21%) and carbohydrates (39%) were recorded in the batch process with species Scenedesmus obliquus. In all of the experiments, the Linolenic acid concentration (C18:3) was greater than 12%, achieving satisfactory oxidative stability and good quality. Projected biofuel production could vary between 4,863,708 kg and 9,246,456 kg year⁻¹ if all the dairy wastewater produced in Brazil were used for this purpose. Two hectares would be needed to produce 24,99 × 109 L year⁻¹ of microalgae bioethanol, a far lower value than used in cultivating sugar cane. If all dairy wastewater generated annually in Brazil were used to produce microalgae biomass, it would be possible to obtain approximately 30,609 to 53,647 barrels of biodiesel per year. These data show that only by using dairy wastewater would biofuels be produced to replace 17% to 40% of the fossil fuels currently used in Brazil.]]></description>
      <pubDate>Mon, 28 Mar 2022 10:28:01 GMT</pubDate>
      <guid>https://trid.trb.org/View/1922175</guid>
    </item>
    <item>
      <title>Methodology for robustness analysis to supply chain disruptions</title>
      <link>https://trid.trb.org/View/1728196</link>
      <description><![CDATA[The objective of this paper is to develop a dynamic mixed integer linear programming model (MILP) of analysis of robustness to supply chain disruptions. The proposed approach allows analysing different causes of disruptions for supply chains, and how these interruptions prevent the bottom-of-the-pyramid (BoP) organisations from fulfilling their purpose of eradicating poverty. Critical operational performance indicators were used to evaluate the impacts of interruptions at the beginning of the supply chain and their implications for the BoP organisations. The authors consider different types of disruptions that mainly affect the first links of the chain of the BoP. In addition, the proposed approach measured the impact of the demand satisfaction of final products for the same population. The efficiency of the proposed approach has been tested using real data obtained from a dairy supply chain management in Cundinamarca (Colombia). The obtained results show the benefits of the proposed model.]]></description>
      <pubDate>Fri, 11 Sep 2020 17:31:23 GMT</pubDate>
      <guid>https://trid.trb.org/View/1728196</guid>
    </item>
    <item>
      <title>Making dairy supply chains robust against corruption risk : a systemic exploratory study</title>
      <link>https://trid.trb.org/View/1677462</link>
      <description><![CDATA[]]></description>
      <pubDate>Tue, 07 Jan 2020 11:25:10 GMT</pubDate>
      <guid>https://trid.trb.org/View/1677462</guid>
    </item>
    <item>
      <title>A stochastic dairy transportation problem considering collection and delivery phases</title>
      <link>https://trid.trb.org/View/1650749</link>
      <description><![CDATA[Based on the dairy cooperatives in Indonesia, this study formulates a stochastic programming model to handle the milk collection and delivery process with the maximum route duration limitation, the external cooling facility option, and travel time uncertainty. Besides, the local practice of sharing the fleet for both collection and delivery further complicates the decision. A set covering-based solution approach is used, due to its flexibility in handling complicated operational requirements and alignment with the decision environment. According to the numerical experiment, the proposed solution algorithm can provide quality solutions with a reasonable computational time for the cooperative operators.]]></description>
      <pubDate>Fri, 27 Sep 2019 17:03:59 GMT</pubDate>
      <guid>https://trid.trb.org/View/1650749</guid>
    </item>
    <item>
      <title>Land O'Lakes locks in Texas-based capacity : faced with the challenge of securing capacity in specific lanes, the iconic company broke with tradition and teamed up with Uber Freight to take a technology-based approach to improve service</title>
      <link>https://trid.trb.org/View/1585309</link>
      <description><![CDATA[]]></description>
      <pubDate>Tue, 19 Feb 2019 14:51:33 GMT</pubDate>
      <guid>https://trid.trb.org/View/1585309</guid>
    </item>
    <item>
      <title>A rich heterogeneous fleet vehicle routing problem with flexible time windows: a case study of dairy supply chain</title>
      <link>https://trid.trb.org/View/1517452</link>
      <description><![CDATA[Routing is a particularly important concept of cargo transport and has always enticed the interest of researchers and decision makers from different industries. The rich vehicle routing problem considers more realistic features of the real-world problems than the conventional problem. This article aims at solving a vehicle routing problem with heterogeneous fleet and flexible hard and soft time windows where flexible time windows allow for early and tardy deliveries in a given tolerance interval considering earliness and tardiness penalties through defining the earliness and tardiness as decision variables. In this paper, the proposed mathematical programming model is verified through several numerical examples using GAMS software. In order to demonstrate the applicability of the model, a real-world case study is provided. The results show the high potential of the proposed model for real-life application. Specifically, by applying the results of the case study, a 156,000 USD annual cost reduction is possible.]]></description>
      <pubDate>Thu, 19 Jul 2018 14:45:31 GMT</pubDate>
      <guid>https://trid.trb.org/View/1517452</guid>
    </item>
    <item>
      <title>An integrated production-distribution planning of dairy industry – a case study</title>
      <link>https://trid.trb.org/View/1515321</link>
      <description><![CDATA[In dairy, where the product shelf life is too short, integrated production and distribution (P-D) planning is one of the important decision making area. This paper basically discusses one such P-D planning of an Indian milk industry. A three-echelon supply chain model is developed including suppliers, plant and retailers. Fluid milk products and milk made products are the two product families that are produced by the plant, where several important issues are considered with P-D planning like, deterioration rate of raw milk and final products, cost related issues of raw milk, transportation, collection, production, inventory, set up, and time related issues in late or early delivery of the final products to retailers. This model, in fact includes both production scheduling and distribution scheduling. A mixed integer linear programming (MILP) model is used to formulate the above situation to maximise the overall profit contribution of the business. The MILP is solved by using Optimization Programming Language (OPL) in CPLEX, and a comparison is made with the current business situation and the improved condition through sensitivity analysis of the collection; production and distribution parameters.]]></description>
      <pubDate>Fri, 15 Jun 2018 09:37:40 GMT</pubDate>
      <guid>https://trid.trb.org/View/1515321</guid>
    </item>
    <item>
      <title>A comparative analysis of vehicle-related greenhouse gas emissions between organic and conventional dairy production</title>
      <link>https://trid.trb.org/View/1505405</link>
      <description><![CDATA[This paper looks at dairy production, vehicle emissions, and global warming impact. Specifically, it compares the greenhouse gas emissions of organic dairy production versus conventional dairy production. Data was collected from 20 conventional milk producers and 20 organic milk producers in Sweden. Data analyzed included types of machinery required, frequency of use, hectares covered, number of deliveries, volume of goods delivered, and delivery method. In general, organic milk production was found to contribute higher levels of greenhouse gas emissions from vehicle-related fuel consumption than conventional milk production. In addition it was found that although organic milk production reduces road-related transport emissions, this reduction does not offset the higher level of emissions from farmyard vehicles.]]></description>
      <pubDate>Tue, 22 May 2018 11:48:54 GMT</pubDate>
      <guid>https://trid.trb.org/View/1505405</guid>
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