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    <title>Transport Research International Documentation (TRID)</title>
    <link>https://trid.trb.org/</link>
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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>Congestion-aware pick-up and drop-off network design problem</title>
      <link>https://trid.trb.org/View/2698615</link>
      <description><![CDATA[Mobility-On-Demand (MOD) services have been shown to increase traffic congestion, primarily due to the rise in total Vehicle-Kilometers-Traveled. Additionally, frequent short-term stops for passenger Pick-Up and Drop-Off (PUDO) processes further disrupt traffic flow and reduce network capacity. With vehicle automation expected to boost demand for such services, large segments of the transport network could be critically affected by both Autonomous MOD (AMOD) vehicle movement and PUDO activities.This study introduces a novel strategic planning problem for an AMOD service with walking legs, which involves deciding where and how much curb space should be dedicated for PUDO processes and where to prohibit double parking PUDOs. We formulate a multi-objective optimization problem with three goals: minimize traffic congestion, reduce walking times for AMOD users, and limit curbside space consumption. We propose a modular approach with three components: i) an AMOD model with PUDO location and regulation constraints, ii) a static traffic assignment with sensitivity to PUDO frequencies per link, and iii) an upper-level optimization that employs the Adaptive Large Neighborhood Search (ALNS) metaheuristic to identify (near-)optimal PUDO regulation strategies.A case study on a small urban network highlights the importance of accounting for the effects of PUDO processes on the traffic system. The findings suggest that at low AMOD penetration, dedicated PUDO areas may be unnecessary with limited system-wide cost, whereas at higher penetration rates, curbside provision yields significant benefits, e.g., under a 7.5% AMOD demand, allocating 100 strategically placed curbside spaces raises average network speeds by 2 km/h compared to allowing double parking only.]]></description>
      <pubDate>Thu, 27 Aug 2026 16:32:56 GMT</pubDate>
      <guid>https://trid.trb.org/View/2698615</guid>
    </item>
    <item>
      <title>Bicycle Improvement Design Problem using real bike trajectories</title>
      <link>https://trid.trb.org/View/2684664</link>
      <description><![CDATA[The development of low-carbon mobility such as cycling is a crucial issue today, especially in urban areas where the extensive use of cars causes difficulties such as pollution, traffic congestion, and overcrowded parking. Existing literature highlights that a crucial factor in the adoption of bicycle commuting is the availability and density of bike networks (Schoner and Levinson, 2014; Buehler and Dill, 2016). In this context, computational methods can serve as decision support systems to determine how bicycle network should be expanded. Recent years have seen two key technological developments that can be integrated into these systems: (i) collaborative open data platforms such as OpenStreetMap that offer accurate information about cycling networks, and (ii) dedicated navigation apps for cyclists, such as Geovelo [from La Compagnie des Mobilités (Geovelo, 2009)], that record and analyze cycling journeys. In this study, we propose using a set of GPS tracks of the routes taken by cyclists to recommend budget-constrained improvements to cycling networks. Our objective is to determine where bicycle facilities should be located to improve overall user satisfaction. To address this problem we introduce a mathematical model and heuristics. In our approach, we show that individual GPS trajectories can play a crucial role in effectively improving the cycling network. First, the use of origin–destination pairs corresponding to actual trajectories is useful for determining where the network needs to be improved; second, actual bicycle trajectories are used to determine each cyclist’s trade-offs between distance and danger. These individual trade-offs are considered in our optimization model and result evaluation, allowing us to account for the heterogeneity of cyclists. The use of a representative set of trajectories is therefore essential. Experiments using real datasets are presented to evaluate the quality of the proposed methods.]]></description>
      <pubDate>Wed, 01 Jul 2026 09:36:25 GMT</pubDate>
      <guid>https://trid.trb.org/View/2684664</guid>
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    <item>
      <title>50 years of Operations Research for the tactical planning of consolidation-based freight transportation</title>
      <link>https://trid.trb.org/View/2543899</link>
      <description><![CDATA[Consolidation-based freight transportation supports a large and valuable part of world trade, over short, medium, long, and intercontinental distances, which all societies depend on and thrive on. It is carried out by carriers that supply the resources and services that meet the demands expressed by shippers. Consolidation aims at increased operational and economic efficiency, by combining cargo of different shippers into the same loading units for their complete or partial journeys. The scope of this paper is consolidation-based freight transport and the tactical planning challenges faced by carriers, who need to design a set of scheduled services that profitably and efficiently align the allocation of resources with anticipated shipping needs over a medium to long-term horizon. The tactical plan then guides day-to-day operations and informs strategic decisions. Building it represents a very complex problem, however, that requires powerful decision-support tools. Operations Research, O.R., has a long and rich history of fruitful interactions with the decision-making and planning of freight transportation, leading to significant methodological developments and delivering high-quality solutions within the necessary decision-making time frames. The paper focuses on this history, emphasizing the developments in Service Network Design, SND, the primary O.R. methodology proposed to address the challenges of tactical planning problems pertinent to consolidation-based freight transportation systems. The paper is structured to explore key dimensions in the inherent complexity of carrier tactical planning and the SND innovations developed to address them. These dimensions include the explicit consideration of temporal aspects of system elements and dynamics; integrative decision making, particularly in managing the resources carriers require to support their services and operations; and accounting for the uncertainty that directly impacts the planning of consolidation-based freight transportation systems. The paper offers insights into the main developments over the last 50 years and identifies promising research avenues.]]></description>
      <pubDate>Fri, 20 Jun 2025 11:58:43 GMT</pubDate>
      <guid>https://trid.trb.org/View/2543899</guid>
    </item>
    <item>
      <title>The service network design problem with fleet and emissions management</title>
      <link>https://trid.trb.org/View/2409045</link>
      <description><![CDATA[The authors propose the Service Network Design Problem with Fleet and Emissions Management (SND-FEM). This problem considers fleet management decisions regarding how many vehicles of each type (diesel, electric, hydrogen) a carrier should acquire as well as in what regions they should operate. The impact of these fleet-level decisions on customer service is captured by explicitly modeling the routing of shipments and vehicles while recognizing the consumption of limited onboard resources (diesel fuel, electrical energy, hydrogen). Thus, the problem also prescribes resource replenishment decisions, with an explicit recognition that the emissions and costs associated with resource replenishment can vary by region. The environmental impact of problem decisions is captured with a detailed accounting of Well-to-Wheel (WtW) emissions based on the framework proposed by the Global Logistics Emissions Council, a methodology that has become the industry standard. The authors propose a Mixed Integer Programming (MIP) formulation of the problem and consider two objectives: (i) transportation cost, and (ii) WtW emissions. With a case study based on carefully collected data from government and industry sources, the authors elaborate the potential of including novel power-train technologies in heavy-duty truck fleets to reduce both cost and emissions-based fleet performance measures.]]></description>
      <pubDate>Thu, 22 Aug 2024 15:11:11 GMT</pubDate>
      <guid>https://trid.trb.org/View/2409045</guid>
    </item>
    <item>
      <title>Robust Optimization Approach for Transportation Network Design under Demand Uncertainty</title>
      <link>https://trid.trb.org/View/2203788</link>
      <description><![CDATA[This paper reviews the authors' recent developments on applying a robust optimization approach to transportation network design problems where future travel demands are uncertain and traffic flows on the underlying network are in user equilibrium. The authors assume that the travel demands belong to an uncertainty set instead of having them follow some probability distributions and then design the network against the worst-case scenario realized in the set. The problems are formulated as mathematical programs with complementarity constraints, which are efficiently solvable by a cutting-plane scheme. Numerical examples are provided to demonstrate that the designs from the robust optimization approach perform more stably and guard better against worst-case scenarios than those from traditional deterministic approach.]]></description>
      <pubDate>Thu, 18 Jul 2024 10:49:00 GMT</pubDate>
      <guid>https://trid.trb.org/View/2203788</guid>
    </item>
    <item>
      <title>Incorporating travel time means and standard deviations into transportation network design problem: a hybrid method based on column generation and Lagrangian relaxation</title>
      <link>https://trid.trb.org/View/2337234</link>
      <description><![CDATA[Travel times in real-world transportation networks are affected by many disruptions. When we conduct the network design optimization, the traffic condition and its resulting travel time variability should be taken into account. However, most of the previous network design optimizations adopted the lengths or expected travel times of links. Based on travel time means and standard deviations, we develop an arc-based model that is a nonlinear and concave integer program. By the Dantzig-Wolfe reformulation, we transform it into an equivalent column-based model that is an integer linear program with a large number of variables. Based on the column-based model, we develop a hybrid method based on column generation and Lagrangian relaxation. The restricted master problem can be settled by the linear programming solvers. The pricing subproblems incorporate independent reliable shortest path problems and a knapsack problem. In numerical experiments, the proposed method can generate feasible solutions with good integrality gaps.]]></description>
      <pubDate>Thu, 22 Feb 2024 16:14:02 GMT</pubDate>
      <guid>https://trid.trb.org/View/2337234</guid>
    </item>
    <item>
      <title>New formulations for the Scheduled Service Network Design Problem</title>
      <link>https://trid.trb.org/View/2155011</link>
      <description><![CDATA[The authors propose a new approach to formulating the Scheduled Service Network Design Problem (SSNDP) that involves modeling with enumerated consolidations of shipments routed on the physical network. This is in contrast to the classical approach of capturing the synchronization of vehicles and shipments needed for consolidation with a time-expanded network. The proposed formulation has both a stronger linear relaxation and is less symmetric. The authors present multiple speed-up techniques and with an extensive computational study illustrate that the consolidation-based formulation is much easier to solve with an off-the-shelf mixed integer programming (MIP) solver than the classical formulation based on a time-expanded network. To avoid instances involving large numbers of consolidations the authors propose a hybrid formulation that combines ideas from the consolidation and time-expanded network-based approaches to formulating the SSNDP. The authors show that instances of the hybrid formulation are much easier to solve than both instances of the pure consolidation-based formulation and those based on a time-expanded network formulation. Finally, the authors discuss how formulating with consolidations facilitates modeling issues that have not yet been addressed in the literature, such as bin-packing considerations when computing vehicle capacity needs. In addition, the proposed modeling technique for bin-packing considerations in a consolidation-based formulation yields instances that are easier to solve than those wherein capacity is modeled in an aggregate sense.]]></description>
      <pubDate>Mon, 26 Jun 2023 12:41:32 GMT</pubDate>
      <guid>https://trid.trb.org/View/2155011</guid>
    </item>
    <item>
      <title>A survey on the transit network design and frequency setting problem</title>
      <link>https://trid.trb.org/View/1990694</link>
      <description><![CDATA[Appropriate public transport systems are crucial in modern cities. Given the high costs that they represent and the impact they have on people’s lives, effective tools are required to support their design. With this in mind, the Transit Network Design problem (TNDP) and the Transit Network Design and Frequency Setting problem (TNDFSP) have been extensively studied in the domain of Operations Research. However, due to the complexity of these problems, multiple simplifications are typically made when modelling and designing solution algorithms. Therefore, still no optimization techniques are available to address these problems in practice. Moreover, different studies address different versions of the problem, with varying assumptions and constraints, complicating the comparison of results or solution approaches. This paper presents an extensive survey of studies addressing the TNDP and the TNDFSP. It discusses the different assumptions, constraints, objectives, solution approaches and testing instances that have been considered in the literature. Furthermore, a detailed analysis is done regarding the case studies considered for the TNDFSP. Moreover, the variants of the passenger assignment subproblem that have been applied within the TNDP and the TNDFSP are discussed. The analysis shows that extensive research has been done regarding these problems. However, it also identified the significant gap that still exists between theory and practice, even in the studies addressing case studies.]]></description>
      <pubDate>Thu, 21 Jul 2022 11:30:36 GMT</pubDate>
      <guid>https://trid.trb.org/View/1990694</guid>
    </item>
    <item>
      <title>Assessing Long-Term Impacts of Automation on Freight Transport and Logistics Networks: Large-Scale LRP Integrated in Microscopic Transport Simulation</title>
      <link>https://trid.trb.org/View/1927216</link>
      <description><![CDATA[Up to now, bulk transports have been carried out via a hub-and-spoke network in the general cargo sector. However, it is expected that the use of autonomous vehicles will enable a more flexible delivery. Such developments may, economically, make sense for shippers. From an ecological point of view, also negative effects can be expected due to enhanced transport performance. In the framework of this research, the authors investigate the impacts of automation on general cargo transport at the logistics network level. For assessing the impacts of autonomous vehicles on logistics network structures and on freight transport routes ex-ante, an instrument for strategic transport and logistics network planning is needed. The authors develop an effective heuristic to find new facilities and adjust the network, while thereby considering the routing characteristics by tackling the large-scale location routing problem (LRP). By the linked approach, the authors can optimize the logistics network and also measure exact transport distances, driving transport lead times and number of necessary vehicles on the infrastructure network. The authors operationalize this approach in the framework of a case study focusing on the food retail distribution in Germany. In fact, this research reveals that the utilization of autonomous vehicles significantly enhances transportation ranges and the number of tours, while reducing the number of operating facilities.]]></description>
      <pubDate>Wed, 13 Apr 2022 09:37:41 GMT</pubDate>
      <guid>https://trid.trb.org/View/1927216</guid>
    </item>
    <item>
      <title>Transit network design using a genetic algorithm with integrated road network and disaggregated O–D demand data</title>
      <link>https://trid.trb.org/View/1768698</link>
      <description><![CDATA[Evolutionary algorithms have been used extensively over the past 2 decades to provide solutions to the Transit Network Design Problem and the Transit Network and Frequencies Setting Problem. Genetic algorithms in particular have been used to solve the multi-objective problem of minimizing transit users’ and operational costs. By finding better routes geometry and frequencies, evolutionary algorithms proposed more efficient networks in a timely manner. However, to the knowledge of the authors, no experimentation included precise and complete pedestrian network data for access, egress and transfer routing. Moreover, the accuracy and representativeness of the transit demand data (Origin Destination matrices) are usually generated from fictitious data or survey data with very low coverage and/or representativity. In this paper, experiments conducted with three medium-sized cities in Quebec demonstrate that performing genetic algorithm optimizations using precise local road network data and representative public transit demand data can generate plausible scenarios that are between 10 and 20% more efficient than existing networks, using the same parameters and similar fleet sizes.]]></description>
      <pubDate>Tue, 27 Apr 2021 09:28:01 GMT</pubDate>
      <guid>https://trid.trb.org/View/1768698</guid>
    </item>
    <item>
      <title>Integrating Fixed and Demand-responsive Transportation for Flexible Transit Network Design</title>
      <link>https://trid.trb.org/View/1759155</link>
      <description><![CDATA[In cities around the world, transit is currently provided with fixed route transportation only, whence the inherent limited Quality of Service (QoS) for travelers in suburban areas and during off-peak. On the other hand, it has been shown that completely replacing fixed-route with demand-responsive transit fails to serve the high transportation demand during peak hours. Therefore, it is still unclear how one can maximize the potential of demand-responsive transit by satisfying the complicated demand pattern varying with time and space. In this paper the authors propose Flexible Transit, a transit system design which gets the best from fixed-route and demand-responsive transit, depending on the demand observed in each sub-region of the urban conurbation and time-of-day. The goal is to provide high transportation capacity while guaranteeing high QoS, two objectives that are instead conflicting with classic fixed-schedule transportation. To this end, the authors first resort to microsimulation to show the limits of using either only fixed-route buses or only demand-responsive buses. This motivates the need of alternating between them instead, which the authors do in Flexible Transit. The authors then resort to Continuous Approximation to find the optimal design of flexible transit. The authors show that the flexible transit can significantly improve the user costs, in particular in suburban areas, while also reducing the overall cost of user and operator. The authors believe their findings suggest important policy insights in designing and planning of future transit systems, to take full advantage of demand-adaptive transportation modes.]]></description>
      <pubDate>Thu, 04 Feb 2021 16:48:12 GMT</pubDate>
      <guid>https://trid.trb.org/View/1759155</guid>
    </item>
    <item>
      <title>Can travel time variability be ignored when solving the transit network design problem?</title>
      <link>https://trid.trb.org/View/1669851</link>
      <description><![CDATA[Due to the ever-increasing demand for transportation, and the resulting congestion in urban areas, the efficient design of transit systems nowadays is more relevant than ever before. In order to attract users, transit systems should deliver an added benefit. Improving transit systems can assist in encouraging the public to abandon their private vehicle and make an increasing use of transit. This in turn will support generating more sustainable and less congested transportation systems. Numerous studies have been dedicated to the Transit Network Design Problem (TNDP), each of which manifested other aspects of the problem, and suggested different solution approaches. A common division identifies a sequence of 5 decisions, covering different related aspects of the problem: the design of the routes, setting frequencies, timetable development, bus scheduling and driver scheduling. This paper discuss the first two stages, namely, designing the routes of the system and setting their frequencies, referred in several previous studies as the Transit Network Design and Frequencies Setting Problem. The main contribution of this study lies in proposing a new formulation for the TNDFSP, a formulation which is based on the solution of the user equilibrium, and therefore increases the reliability of the model by capturing travel time variability. Moreover, this study provides means for assessing the correctness of the assumption underlying previous models, suggesting that travel time variability can be neglected while solving the TNDFSP.]]></description>
      <pubDate>Fri, 20 Dec 2019 16:24:09 GMT</pubDate>
      <guid>https://trid.trb.org/View/1669851</guid>
    </item>
    <item>
      <title>Metaheuristics for the transit route network design problem: a review and comparative analysis</title>
      <link>https://trid.trb.org/View/1669619</link>
      <description><![CDATA[This paper critically reviews applications of metaheuristics for solving the Transit Route Network Design Problem (TRNDP). A structured review is offered and prominent metaheuristics for tackling the TRNDP are evaluated, according to a benchmark network. The review findings yield a unified implementation framework, which contains common algorithmic components and different solution representations and methods, which are considered important for obtaining solutions of good quality. The paper concludes with identified gaps in research and opportunities for future research on the application of metaheuristic algorithms for solving the TRNDP.]]></description>
      <pubDate>Fri, 20 Dec 2019 16:23:15 GMT</pubDate>
      <guid>https://trid.trb.org/View/1669619</guid>
    </item>
    <item>
      <title>Optimization of Emergency Traffic Patrols (ETP) Operations</title>
      <link>https://trid.trb.org/View/1647058</link>
      <description><![CDATA[Effective incident management relies on many tools to lessen the overall impact of crashes, road debris, and disabled vehicles. Many urban areas have adopted freeway service patrol (FSP) programs that patrol the freeway network searching for incidents, providing aid to motorists, and assisting with incident management and clearance. FSP management must consider the beat configuration, fleet size, and fleet allocation. The beat configuration is how the network is divided into different parts for patrolling, and each part is called a beat. The beat configuration, fleet size, and fleet allocation need to be determined for designing a network for FSP program. This research presents a comprehensive mixed-integer programming model to design the network for freeway service patrol programs. This model aims to concurrently determine the beat structure, fleet size, and allocation of trucks to beats, to minimize incident delay while the operational cost is considered, as well. The proposed model is tested using data from part of the Tarrant County Courtesy Patrol (CP) network in Texas. Also, to explore the problem with field data and real-size networks, the proposed model and developed heuristics are applied to part of the freeway network in Maryland covered by Coordinated Highways Action Response Team (CHART). Results indicate that a joint model forms a better solution regarding incident delay reduction and operation costs.]]></description>
      <pubDate>Tue, 27 Aug 2019 12:53:37 GMT</pubDate>
      <guid>https://trid.trb.org/View/1647058</guid>
    </item>
    <item>
      <title>Integrated Railway Rapid Transit Network Design and Line Planning problem with maximum profit</title>
      <link>https://trid.trb.org/View/1605663</link>
      <description><![CDATA[The authors solve the Integrated Network Design and Line Planning Problem in Railway Rapid Transit systems with the objective of maximizing the net profit over a planning horizon, in the presence of a competing transportation mode. Since the profitability of the designed network is closely related with passengers’ demand and line operation decisions, for a given demand, a transit assignment is required to compute the profit, calculating simultaneously the frequencies of lines and selecting the most convenient train units. The proposed iterative solving procedure is governed by an adaptive large neighborhood search metaheuristic which, at each iteration, calls a branch-and-cut algorithm implemented in Gurobi in order to solve the assignment and network operation problems. The authors provide an illustration on a real-size scenario.]]></description>
      <pubDate>Mon, 29 Jul 2019 11:03:28 GMT</pubDate>
      <guid>https://trid.trb.org/View/1605663</guid>
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