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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>
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      <title>Transport Research International Documentation (TRID)</title>
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    <item>
      <title>A logistics cost function with explicit transport costs</title>
      <link>https://trid.trb.org/View/1635717</link>
      <description><![CDATA[With a view to construct a new framework to assess the benefits of freight transport improvements, an Economic Order Quantity model with uncertain lead time demand is equipped with detailed transport costs. The problem is to minimise total logistics cost by choosing shipment size, vehicle size and reorder point subject to constraints on vehicle size and annual transport capacity. An analytical solution in all variables except the reorder point is derived, reducing the cost minimisation problem to a well-behaved problem in one dimension only.Different parts of transport costs influence the solution differently: Some act like ordering costs, some like holding costs and some have no influence on the solution. The solution exhibits economies of scale at all levels of optimal shipment size.Examples with real data show that model calibration for an entire population of firms is feasible at the firm level, and that the model produces reasonable results.]]></description>
      <pubDate>Mon, 22 Jul 2019 08:00:11 GMT</pubDate>
      <guid>https://trid.trb.org/View/1635717</guid>
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    <item>
      <title>The effects of using different output measures in efficiency analysis of public transport operations</title>
      <link>https://trid.trb.org/View/1595032</link>
      <description><![CDATA[There is growing interest in measuring efficiency and productivity in the public sector. Most commonly this is done using data envelopment analysis (DEA) or Stochastic frontier analysis (SFA) to determine the level of (in)efficiency of different decision-making units. These methods have also been applied to public transport. However, in this context their application presents some problems, including how to define what is produced and how that should be measured. Several options have been suggested including vehicle-kilometres, number of trips, number of passenger-kilometres, and scores in passenger satisfaction surveys.The primary aim of this paper is to discuss how production of public transport should be defined and measured in efficiency studies. It is argued that output should be measured by number of trips and vehicle-kilometres as these together represent consumers' willingness to pay for public transport services.A proposed model for evaluating the efficiency of public transport operations is presented and estimated. This model is evaluated by comparing its results to those obtained from competing models estimated using the same data from 27 Swedish counties from 1986 to 2015. The data are used to estimate stochastic cost frontier models and it is concluded that the models using only vehicle-kilometres or only passenger trips tend to underestimate efficiency compared to a model using both at the same time. It is also concluded that smaller models (using only a single output measure) result in different rankings of the decision-making units.]]></description>
      <pubDate>Fri, 29 Mar 2019 10:15:28 GMT</pubDate>
      <guid>https://trid.trb.org/View/1595032</guid>
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    <item>
      <title>An experimental analysis of Mediterranean supply chains through the use of cost KPIs</title>
      <link>https://trid.trb.org/View/1550000</link>
      <description><![CDATA[Over the last twenty years, the intensification of trade flows and the rapid growth of demand for goods and services from new emerging countries have led to a deep change in global transport and a dramatic increase in the level of competitiveness among transportation and logistics service providers. To remain competitive, transport and logistics operators are required to carry out operations with maximum efficiency to meet the requirements of a continually growing and diversified demand. Supply Chain Management is one of the areas that have recently attracted much attention in logistics. The proposed study aims to provide simple quantitative tools based on Key Performance Indicators (KPIs) to support the evaluation process of intermodal supply chains. A sample of 44 real-world Mediterranean supply chains has been collected and analyzed. Four quantitative KPIs describing the relationship time-cost and the ratio cost/kilometer have been derived from empirical cost functions and used to characterize the various elements of the analyzed transport chains, and of the chains as a whole, from a cost perspective.]]></description>
      <pubDate>Tue, 20 Nov 2018 10:24:10 GMT</pubDate>
      <guid>https://trid.trb.org/View/1550000</guid>
    </item>
    <item>
      <title>Cost functions and multi-objective timetabling of mixed train services</title>
      <link>https://trid.trb.org/View/1515442</link>
      <description><![CDATA[This paper investigates a set of cost functions for assessing and timetabling mainline train services. The present study incorporates considerations from both operators’ and passengers’ perspectives including service running times, punctuality, waiting times, and comfort of the journeys. The cost functions are applied to a multi-objective optimisation formulation subject to constraints representing operational requirements and signalling systems. The optimisation model is applied to the Brighton Main Line network in Southeast England as a case study, and the results demonstrate how the proposed optimisation framework can help government and train operators to derive more effective and equitable timetable with consideration of customer satisfaction. A Pareto analysis is further derived to illustrate the trade-off between conflicting objectives in the optimisation process under different circumstances.]]></description>
      <pubDate>Wed, 27 Jun 2018 10:42:11 GMT</pubDate>
      <guid>https://trid.trb.org/View/1515442</guid>
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      <title>Development of Hybrid Cost Functions From Engineering and Statistical Techniques: The Case of Rail - Phase II Final Report</title>
      <link>https://trid.trb.org/View/1497866</link>
      <description><![CDATA[Cost analysis is important in every transportation industry, to the firms or agencies which provide service, to regulatory bodies, and to public policy makers. In the past, railroad cost analyses have been of two types: 1) statistical analyses of aggregate cross-section data from a variety of firms, or 2) very detailed operations-oriented studies. The premise of the work reported here is that a "hybrid" approach, using both economic theory and statistical methods on the one hand, and engineering analysis of operations on the other, can produce superior results. This report covers Phase II of the project, which focused on analysis of a major class I railroad. A short-run variable cost function was estimated econometrically, and used as a basis for deriving the associated long-run function. The authors also developed a simple, but relatively accurate, network model to estimate operating costs. This model may be used to estimate origin-destination specific marginal operating costs. Econometric analysis of the output from the model leads to a theoretically justifiable equation for predicting marginal operating costs, and their sensitivity to changes in flows and input prices.]]></description>
      <pubDate>Sun, 11 Feb 2018 18:33:58 GMT</pubDate>
      <guid>https://trid.trb.org/View/1497866</guid>
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    <item>
      <title>Cost functions and determinants of unit cost effects in horizontal airline M&amp;As</title>
      <link>https://trid.trb.org/View/1479943</link>
      <description><![CDATA[This paper analyses the unit cost effects of mergers and acquisitions (M&As) using linear, quadratic, and translog cost functions. In addition to a basic unit cost model the authors specify separate models for distress, profit, relative size, and cost difference, among the merging firms. The authors use a sample of 19 horizontal M&As in the international airline industry and data spanning from 1980 to 2012. The authors' models show that M&As do not affect unit costs in a significant way, unless the relative size difference of the merging firms is large, in which case the authors detect an increase in unit costs.]]></description>
      <pubDate>Tue, 29 Aug 2017 10:07:30 GMT</pubDate>
      <guid>https://trid.trb.org/View/1479943</guid>
    </item>
    <item>
      <title>In the Peleton or in the Break - Factors Affecting Cyclists Route Choice in London</title>
      <link>https://trid.trb.org/View/1452923</link>
      <description><![CDATA[‘The Mayor’s Vision for Cycling in London' sets out an ambitious programme of investment in cycling. In order to support this, Transport for London has been developing its analytical capability to better appraise the impacts of cycling infrastructure. This will help to understand better where investment in cycling should be prioritised, The study which is the focus of this paper aimed to provide key insight into how cyclists choose their route for implementation in TfL’s new cycling route choice model. The key objectives of this study were to: 1) Provision of parameters or values for a Generalised Cost (GC) function in a network-based cycle route choice model, segmented as appropriate to best explain observed behaviour; and 2) Provide outputs which are compatible for incorporation into TfL’s network based model of cyclist route choice (CYNEMON). The study was undertaken in six stages: 1) A Literature Review of past studies, including two Revealed Preference (RP) studies in Zurich and San Francisco, plus a number of Stated Preference (SP) studies; 2) A Stage 1 survey to recruit respondents and gain detailed socio-demographic and travel pattern characteristics for later segmentation analysis; 3) A Stage 2 data collection exercise, where recruited respondents recorded their cycle journeys in London; 4) A Stage 3 survey, to help validate the findings of the choice modelling, where respondents were asked to explain their observed choices; 5) Build of a detailed GIS network of cycle links in London, including the mapping of multiple possible explanatory variables to a spatially detailed network; and 6) Route choice models for the observed journeys, involving the generation of alternative routes to create a ‘choice set’, examination of different combinations of explanatory variable, and the transformation of outputs suitable for implementation in CYNEMON. In comparison to assignment of motor vehicles in highway assignment modelling, which typically focuses on time and cost [based on distance] attributes, cycle route choice decision-making is perceived to be influenced by both different, and a greater number of attributes. In the UK it is a relatively under-researched field, reflecting the relatively low mode share for cycling in recent decades and a historic, relative to the present day, lack of policy focus during that period. This environment has now shifted markedly, with an increased recognition of the economic, health, and social benefits associated with increasing the proportion of trips made by cycling. In Stage 2, 8,663 observed routes were collected from 774 unique users of the App. These were then subject to a set of automated cleaning processes with the aim of identifying routes with a significant volume of signal loss, missing links (e.g. where there is no network), potential walking (slow average speed), potential transit use (high average speed), and deviation between the observed route and that created using best path analysis. The resulting choice models explaining a high degree of the variance in the choice set, with adjusted rho-squared statistics of 0.89, and showed the following factors to have a statistically significant influence on route choice: 1) Distance; 2) Proportion of route on different classifications of link, e.g. A Road, Minor Road, Canal or Park route etc.; 3) Proportion of the route with different types of cycle infrastructure, including on and off highway provision and the availability of bus lanes; 4) One-way restrictions in the absence of a dedicated contraflow for cyclists; 5) Proportion of route which is signed; 6) Average annual 12 hour, bi-directional, traffic volume; and 7) Total metres gained or lost per 100m. The absence of any junction/node/turn specific attributes ran against prior hypotheses, although the final set of attributes did accord with the findings of the two user surveys. The authors believe that this finding is a result of collinearity in the dataset, the relative quality/spatial accuracy of the datasets available, and also the choice set generation process – where prior assumptions on the attributes of interest are required to create alternative routes. Finally, for implementation in an assignment model, the parameters from the choice model had to be reconciled from a route based level to a link and node level in a network with over 470,000 unique components. The authors conclude by reporting on calibration and validation stages in CYNEMON, and the recommended next steps for London and in this field more generally.]]></description>
      <pubDate>Mon, 13 Feb 2017 09:18:53 GMT</pubDate>
      <guid>https://trid.trb.org/View/1452923</guid>
    </item>
    <item>
      <title>A Web Based Platform Which Help Individuals and Companies Move Commodities with the Most Environmental Friendly Way, Minimizing Emissions and Transportation Cost</title>
      <link>https://trid.trb.org/View/1406898</link>
      <description><![CDATA[The objective of the proposed research is to develop a Decision Support System (DSS) for a web based platform which will help individuals and companies move commodities in the most environmentally friendly way, minimizing environmental externalities (e.g. CO₂ emissions) and transportation costs. The developed platform which is the final outcome of an FP7 European research project, referred to as the GreenRoute project, uses existing information systems (e.g. geographical, weather, real time traffic information systems) and emissions calculation models as a basis to apply two main scientific outcomes. The first scientific outcome is the development of a function that assigns a score to each arc of a transportation network referred to as the arc environmental externalities score (EESarc). The second scientific outcome is the development of a novel approach for solving the general travelling salesman problem (TSP) whose objective is to find the most environmental friendly route. In the frame of this research work, the authors consider the TSP in a connected graph driven by a novel cost function related to environmental factors. The cost function describes with a novel way the environmental impact of the feasible routes. This score approximates the impact of environmental externalities over the specific route. EESarc is uncorrelated to other fuel consumption factors such as the type of vehicle, the weight load and the operating conditions of the vehicle, and depends solely on the traffic conditions; the infrastructure profile; the weather conditions; and the length of each arc. The authors seek a path passing from all intermediate user-defined points minimising the sum of the EESarc for each arc employed in the solution. In order to accelerate solution times in the afore-mentioned context, the authors seek to identify novel modelling and solution approaches. They consider the Euclidean asymmetric TSP as a base model to work on. The authors keep the integrality constraints on the binary variables of the original problem intact and introduce additional integer variables for each node which provide the number of outgoing and ingoing arcs of two given disjoint sets. The authors relax the subtour elimination constraints and enforce valid separation inequalities for the start-up solution. These separation inequalities are generic and do not depend on the specific problem considered. Their number is equal to the number of nodes in the network, resulting in a few but dense rows in the simplex tableau. At each iteration of the algorithm, the authors inspect the solution yielded by the relaxed problem and identify subtours. For every subtour, separation cuts are added to the relaxed problem. The number of cuts is low but their density is high. The authors observe the solution times on a TSP testbed which includes randomly generated instances as well as problems coming from the well -known TSPLIB. They compare their results against several formulations. The authors observe that especially for medium to large networks of some hundreds of nodes, their approach is dominant in terms of solution time over every other one they have considered.]]></description>
      <pubDate>Tue, 31 May 2016 09:14:14 GMT</pubDate>
      <guid>https://trid.trb.org/View/1406898</guid>
    </item>
    <item>
      <title>Freeway Traffic Control Considering Capacity Drop Phenomena: Comparison of Different MPC Schemes</title>
      <link>https://trid.trb.org/View/1406168</link>
      <description><![CDATA[This paper proposes different Model Predictive Control (MPC)-based traffic controllers in order to reduce congestion in freeway systems via ramp metering. These controllers differ for the adopted prediction model and for the considered cost function to be minimized. In particular, both a standard cell transmission model (CTM) and a CTM modified version representing the capacity drop phenomenon are used, while the two different cost functions considered penalize congested states in different ways. These MPC controllers are compared via simulation, both evaluating the performances of the controlled freeway system in the different cases, and from a computational point of view.]]></description>
      <pubDate>Sun, 22 May 2016 18:35:10 GMT</pubDate>
      <guid>https://trid.trb.org/View/1406168</guid>
    </item>
    <item>
      <title>Calibration of Dynamic Traffic Assignment in Managed Lane Facilities Utilizing Detailed Detector and Toll Data</title>
      <link>https://trid.trb.org/View/1338229</link>
      <description><![CDATA[Effectively planning and operating managed lane (ML) facilities requires advanced modeling methods to provide a more accurate assessment of the impacts that changing traffic flow conditions and operation strategies have on system performance and ML utilization. This study examines two different approaches, in combination with static and dynamic traffic assignment, for modeling route choice behaviors: the generalized cost function approach and the willingness-to-pay approach. The study also illustrates the calibration of the parameters of these modeling approaches based on detailed real-world traffic detector and toll data. For the generalized cost function approach, the value of time (VOT) is the most important parameter to calibrate. In addition to travel time savings, VOT partially accounts for the values of reliability, safety, and convenience, which are not easy to measure directly. VOT is estimated to be $42 for the case study corridor. The shape of the willingness-to-pay curve is an important parameter in the willingness-to-pay approach. This study demonstrates that ML modeling results can be significantly improved by calibrating the curve for local conditions. Results indicate that both approaches produce similar output in terms of predicting the percentage of travelers that use MLs, but the generalized cost function is more straightforward to implement and calibrate, and it also converges better. Dynamic traffic assignment was able to model real-world use of MLs due to its ability to replicate real-world congestion patterns. Static traffic assignment, however, failed to model the congestion patterns and thus was unable to accurately estimate the use of MLs.]]></description>
      <pubDate>Tue, 24 Mar 2015 11:27:10 GMT</pubDate>
      <guid>https://trid.trb.org/View/1338229</guid>
    </item>
    <item>
      <title>A translog cost function of the integrated air freight business: The case of FedEx and UPS</title>
      <link>https://trid.trb.org/View/1306993</link>
      <description><![CDATA[This paper analyzes the cost structure of the integrated air freight business by means of a translog cost function. This allows to extend knowledge on the supply side and to examine if strategies of integrators are consistent with cost structure. The cost function is based on quarterly time-series data from 1990 to 2010 for FedEx and UPS. A total and a variable model are estimated. In addition, a static as well as a dynamic approach is followed. The authors find that integrators exhibit strong scale and density economies in the short and the long term. This result is in line with the aggressive expansion and cooperation strategies pursued by integrators. The authors' results indicate that the concentration in the integrated air freight industry will continue: a concern for industry actors and regulatory agencies.]]></description>
      <pubDate>Thu, 01 May 2014 11:42:03 GMT</pubDate>
      <guid>https://trid.trb.org/View/1306993</guid>
    </item>
    <item>
      <title>An Algorithm for Non-additive Shortest Path Problem</title>
      <link>https://trid.trb.org/View/1289802</link>
      <description><![CDATA[This paper presents a solution methodology for general formulation of the shortest path problem with non-additive continuous convex travel cost functions. The proposed solution methodology is based on outer approximation (OA) algorithm which solves the original problem by iterating between the solution of two optimization problems known as subproblem and a master problem. The authors show that subproblem solution in OA framework for non-additive shortest path problem can be expressed through closed form equations and thus the OA framework can be reduced to solving only the mixed integer linear program of the master problem. Numerical experiments conducted on varying size networks based on different combinations of nonlinear cost functions show the ability and efficiency of the proposed framework in providing the exact global solution.]]></description>
      <pubDate>Sun, 23 Mar 2014 17:49:17 GMT</pubDate>
      <guid>https://trid.trb.org/View/1289802</guid>
    </item>
    <item>
      <title>A Customized Particle Swarm Method to Solve Highway Alignment Optimization Problem</title>
      <link>https://trid.trb.org/View/1226440</link>
      <description><![CDATA[The optimization of highway alignment requires a versatile set of cost functions and an efficient search method for achieving the best design. Because of numerous highway design considerations, this issue is classified as a constrained problem. The article describes how highway alignment optimization is a complex problem because of the infinite number of possible solutions for the problem and the continuous search space. In this study, a customized particle swarm optimization algorithm was used to search for a near-optimal highway alignment, which is a compound of several tangents that consist of circular (for horizontal design) and parabolic (for vertical alignment) curves. The selected highway alignment should meet the constraints of highway design while minimizing total cost as the objective function. The model uses geographical information system (GIS) maps as an efficient and fast way to calculate right-of-way costs, earthwork costs, and any other spatial information and constraints that should be implemented in the design process. The efficiency of the algorithm was verified through a case study using an artificial map as the study region. Finally, the authors applied the algorithm to a real-world example and the results were compared with the alignment found by traditional methods.]]></description>
      <pubDate>Thu, 17 Jan 2013 13:47:58 GMT</pubDate>
      <guid>https://trid.trb.org/View/1226440</guid>
    </item>
    <item>
      <title>Model and Algorithm for Continuous Time-Varying Shortest Path Problem</title>
      <link>https://trid.trb.org/View/1113973</link>
      <description><![CDATA[The shortest path problem is a common problem in traffic areas. In an actual traffic network, arc costs are usually time-varying functions. Under such conditions, the issue of how to find a shortest path is called a time-varying shortest path problem. There is little research on this so far, and the research is all aiming at the following situations: arc costs are discrete time-varying functions, piecewise functions, or probability distribution functions. However, arc costs are often continuous time-varying, and there is hardly any research on the shortest path problem under this condition. Therefore, the authors establish a nonlinear programming model and design a corresponding dynamic Dijkstra algorithm on a continuous time-varying path problem, whose correctness and effectiveness are verified through a case study.]]></description>
      <pubDate>Mon, 31 Dec 2012 17:55:35 GMT</pubDate>
      <guid>https://trid.trb.org/View/1113973</guid>
    </item>
    <item>
      <title>Network Modeling 2012, Volume 2</title>
      <link>https://trid.trb.org/View/1217804</link>
      <description><![CDATA[This issue contains 14 papers concerned with the following aspects of transportation network modeling:  generalized profitable tour problems for online activity routing system; combined distribution-assignment model with applications; bilevel optimization approach to design of bike lane network; network hyperpaths based on transit schedules; an intermodal path algorithm for time-dependent auto network and scheduled transit service; transit network design algorithm; model of passenger flow assignment for urban rail transit; cost functions for strategies in schedule-based transit networks with limited vehicle capacities;  gradient project method for simulation-based dynamic traffic assignment; modeling routing behavior for vacant taxicabs; estimating weights of times and transfers for hyperpath travelers; stochastic user equilibrium for route choice model; resiliency of transportation networks after disasters; and link criticality for day-to-day degradable transportation networks.]]></description>
      <pubDate>Thu, 25 Oct 2012 16:25:47 GMT</pubDate>
      <guid>https://trid.trb.org/View/1217804</guid>
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