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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>
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      <title>Research in Progress (RIP)</title>
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      <title>New Models and Solutions to Vehicle Routing with Cardinality and Distance Constraints</title>
      <link>https://rip.trb.org/View/2703788</link>
      <description><![CDATA[Many emerging transportation and logistics operations are constrained by both the maximum distance a vehicle can travel and the number of customers it can serve before requiring replenishment, recharging, or maintenance. These operational realities motivate the need for new routing optimization models that explicitly integrate distance and cardinality constraints. This project proposes the first comprehensive study of a novel Black-and-White Vehicle Routing Problem (BWVRP), where customer nodes and replenishment nodes are jointly routed across a fleet of vehicles, with replenishment nodes allowed to be visited multiple times. The project will develop new mixed-integer linear programming models and exact branch-and-cut methods to obtain optimal solutions for small and medium-sized instances. To address large-scale instances, efficient heuristic and metaheuristic algorithms will be designed and implemented. In addition to methodological advances, the project will develop a data-driven optimization decision-support tool integrating models, algorithms, and user-friendly interface. 
]]></description>
      <pubDate>Sat, 16 May 2026 11:45:53 GMT</pubDate>
      <guid>https://rip.trb.org/View/2703788</guid>
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    <item>
      <title>Rural Omnichannel Healthcare: A Demand-Centric Approach in Transportation System Design
</title>
      <link>https://rip.trb.org/View/2625868</link>
      <description><![CDATA[Entering its second year, the Rural Omnichannel Healthcare Project aims to enhance rural healthcare equity and accessibility by refining the deployment strategy of Telehealth Kiosks/Booths (TKBs). Grounded in Year 1's evidence, this phase deepens the understanding of the complex underlying demand dynamics for the use of TKBs. In particular, Year 2 aims to better understand both the currently unmet healthcare needs in rural areas and how these needs drive the demand for TKBs. Additionally, it investigates how the use of TKBs correlates with the demand for services at existing healthcare facilities. This phase also examines the geographical factors that influence the adoption and utilization of TKBs, exploring how location affects the effectiveness and popularity of these kiosks in enhancing rural healthcare access. Through rigorous empirical research, we aim to refine distance decay functions that describe how these factors impact healthcare access. These insights will inform the enhancement of our mathematical models, guiding the strategic deployment of TKBs to address the unmet needs and preferences of rural communities effectively. The project is set to offer innovative solutions that realistically improve healthcare access and quality, addressing rural healthcare disparities with precision. Through this comprehensive approach, Year 2 of the Rural Omnichannel Healthcare Project stands to significantly advance our understanding of the complexities of healthcare access in rural areas, bridging critical gaps and fostering a more equitable healthcare landscape.
]]></description>
      <pubDate>Tue, 18 Nov 2025 13:56:10 GMT</pubDate>
      <guid>https://rip.trb.org/View/2625868</guid>
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      <title>Developing Optimization Methods for Maritime Escort Strategies for Littoral and Chokepoint Shipping Lanes</title>
      <link>https://rip.trb.org/View/2499090</link>
      <description><![CDATA[Protecting maritime shipping lanes, particularly vulnerable littoral chokepoints, is critical to maintaining global economic stability. These narrow sea passages connecting major bodies of water are susceptible to disruption, as demonstrated by recent hostile activities in the Red Sea and Strait of Hormuz. This project aims to address the growing complexity of maritime threats by developing mathematical optimization models for allocating limited U.S. military assets to neutralize or alleviate the risk of potential threats. The research will develop mixed-integer programming (MIP) models to determine effective strategies involving a diverse set of protection assets, such as warship escorts, unmanned aerial vehicles, and missile defense systems. The project will specifically focus on minimizing risks to vessels while also optimizing the cost-benefit balance for defending these critical shipping corridors. By collaborating with U.S. Navy stakeholders at the U.S. Northern Command, the findings will support enhanced operational planning, contribute to securing domestic transportation infrastructure, and improve the resilience of the global supply chain. This work seeks to fill a gap in the literature by providing a comprehensive, quantitative approach to maritime defense in the context of modern threats.]]></description>
      <pubDate>Wed, 29 Jan 2025 16:37:47 GMT</pubDate>
      <guid>https://rip.trb.org/View/2499090</guid>
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    <item>
      <title>Optimizing Guardrail Placements along Highways in Utah to Enhance Road Safety and Mitigate Road Departure Crashes</title>
      <link>https://rip.trb.org/View/2387164</link>
      <description><![CDATA[This project focuses on optimizing guardrail placements along highways in Utah to enhance road safety and mitigate road departure (RD) crashes. Utilizing advanced computer vision technologies and Mixed Integer Programming (MIP) models, the research aims to analyze roadside features and crash data to strategically position guardrails. By integrating detailed roadside feature data with historical crash severity information, the project seeks to identify high-risk areas for targeted guardrail installation. This approach promises to not only improve safety outcomes by reducing the frequency and severity of RD crashes but also to ensure cost-effective resource allocation, ultimately contributing to safer highways and preserving public welfare in Utah.]]></description>
      <pubDate>Tue, 04 Jun 2024 13:53:37 GMT</pubDate>
      <guid>https://rip.trb.org/View/2387164</guid>
    </item>
    <item>
      <title>Rural Transportation System Design for Omnichannel Healthcare</title>
      <link>https://rip.trb.org/View/2342036</link>
      <description><![CDATA[Long travel distances and a lack of healthcare facilities provide significant challenges for healthcare in rural areas. Telehealth (online) platforms provide new care options, and omnichannel, or multichannel, healthcare supply chains provide healthcare consumers with choices such as traveling to a hospital or clinic, using telehealth from home, or using conveniently located telehealth kiosks. This research investigates design of a network of telehealth kiosks that can reduce the rural resident travel distance and time, and thereby improve rural healthcare access. The focus is on optimally designing such a network, including determining the number and locations of kiosks. The research team uses data-driven analytical modeling to assess coverage, travel distance and time, and costs for rural residents to reach a kiosk or other healthcare facility. The team considers options with both unstaffed kiosks that provide teleconsultation, as well as kiosks that have scheduled periodic staffing from health professionals (e.g., once every two weeks, or once a month). The team also considers an option to use drones (UAVs) to deliver supplies and medications to telehealth kiosks, thereby providing near-immediate availability of a wide range of medical supplies and medicines. The research first develops strategic analytical models using continuous approximation methods to assess the optimal number of telehealth kiosks to deploy and their dependence on the key costs and healthcare coverage. The team then develops tactical discrete mixed integer linear programming (MILP) models for designing a telehealth kiosk network and apply the models using data for a rural region of Missouri.]]></description>
      <pubDate>Mon, 19 Feb 2024 18:17:59 GMT</pubDate>
      <guid>https://rip.trb.org/View/2342036</guid>
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      <title>Multi-stage Planning for Electrifying Transit Bus Systems with Multiformat Charging Facilities</title>
      <link>https://rip.trb.org/View/1675095</link>
      <description><![CDATA[Although electric transit bus systems (ETBS) present significant benefits, it is challenging for a public transit authority to plan the process of electrifying its bus fleet and continue to operate its mixed fleet cost-effectively. This IDEA project developed a decision support tool for public transit authorities for facilitating the process of electrifying their transit buses. Mathematical models of dynamic wireless charging facilities (DWCF) locations for full electrification and partial electrification (multi-objective optimization), and models for route selection and DWCF locations were developed (multi-stage optimization). Solutions algorithms were exploited to solve large scale multi-stage multi-objective optimization problems. Specifically, given the periodic budget and transit network and features, the tool would provide outcomes at different stages, including (1) which routes the acquired electric buses should serve, (2) where to deploy charging facilities (both plug-in at stations and dynamic wireless charging facilities (DWCF) embedded in road pavement), and (3) what should be the right size of the onboard battery for a specific route. The proposed method was applied to a local transit network, HART, in the Tampa Bay area. For a given scenario, i.e., the transit authority needs to choose five routes to electrify in the first stage and another five in the second stage, the tool identified the best routes to electrify and optimal locations of DWCF in both stages. Following the solutions, the transit authority will bear the minimal total cost of constructing DWCF and energy consumptions in a defined planning horizon. Furthermore, the research team developed a Graphic User Interface (GUI) on a Linux system that consolidated data structure design, solution algorithm implementation, economic analysis, and design result visualization. A user manual was produced to help potential users to understand and become familiar with the tool. Users can perform scenario analysis with this tool by changing setting parameters, such as number of routes to be electrified (or budget constraint), cost of DWCF, price of electricity, etc. 

The final report is available.]]></description>
      <pubDate>Thu, 26 Dec 2019 19:27:53 GMT</pubDate>
      <guid>https://rip.trb.org/View/1675095</guid>
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