A multi-level spatial-temporal model for freight movement: The case of manufactured goods flows on the U.S. highway networks

The spatial production, attraction, and movement of manufactured goods are vital to the economy of a region and country. The U.S. department of transportation also mandates to incorporate continuing and efficient freight movement and infrastructure into statewide and local long range planning. Studies on supply, demand, and transport of manufactured goods by firm, industry, mode, or commodity are vast in the logistics and supply chain literature. However, relatively sparse research is available on aggregated movement or freight on national, state, or local transportation networks. Better understanding and modeling freight movement on highway networks to facilitate local transportation, land use, economic development, and comprehensive planning is at the heart of freight research. Therefore, the major endeavors and novel contributions of this research include a conceptual framework proposed for freight movement research, a multi-level spatial-temporal freight model based upon the social optimum assignment for optimal “from”, “to”, “within”, and “through” freight flows of manufactured goods on the U.S. highway networks, and a set of performance measures designed to reveal states in terms of their competitive advantages in production, attraction, self-sufficiency, or cross-road. The freight flows were first visualized and highlighted by state at the U.S. level, then by county at the state level for Oklahoma, and finally by traffic analysis zone for the Tulsa metropolitan area. The spatial split of freight flows was accomplished through using freight, network, and demographic-economic databases at state, county, and zone scales.     

Cycling in a changed climate

The use of bicycle is substantially affected by the weather patterns, which is expected to change in the future as a result of climate change. It is therefore important to understand the resulting potential changes in bicycle flows in order to accommodate adaptation planning for cycling. We propose a framework to model the changes in bicycle flow in London by developing a negative binomial count-data model and by incorporating future projected weather data from downscaled global climate models, a first such approach in this area. High temporal resolution (hourly) of our model allows us to decipher changes not only on an annual basis, but also on a seasonal and daily basis. We find that there will be a modest 0.5% increase in the average annual hourly bicycle flows in London’s network due to a changed climate. The increase is primarily driven by a higher temperature due to a changed climate, although the increase is tempered due to a higher rainfall. The annual average masks the differences of impacts between seasons though – bicycle flows are expected to increase during the summer and winter months (by 1.6%), decrease during the spring (by 2%) and remain nearly unchanged during the autumn. Leisure cycling will be more affected by a changed climate, with an increase of around 7% during the weekend and holiday cycle flows in the summer months.     

基于广义回归神经网络的铁路货运量预测

针对BP神经网络预测存在局部极小缺陷和收敛速度慢的问题,提出基于广义回归神经网络(GRNN)的预测模型。基于我国1999—2008年铁路货运量的历史统计数据,应用GRNN模型和混沌BP神经网络模型对铁路货运量进行预测。通过两种预测模型的计算结果比较说明,GRNN模型具有良好的收敛性和较高的精度,而且模型结构简单、计算速度快,具有良好的实用性。     

模糊神经网络非线性组合预测在铁路货运量预测中的应用

准确的铁路货运量预测关系到铁路运输的发展,为此提出模糊神经网络非线性组合预测模型,应用三次指数预测模型、灰色理论预测模型、多元回归预测模型的预测值作为模糊神经网络的测试样本数据库,输出样本为铁路货运量,并采用全局优化的粒子群算法优化模糊神经网络的参数。仿真结果表明该模型能够取得比单项预测模型更高的精度。     

Intermodal logistics: The interplay of financial,operational and service issues

This research addresses strategic planning for an interregional, hub based, intermodal logistics network operated by a logistics service provider. A tabu search meta-heuristic is used to solve a mathematical optimization model that extends the p-hub median model for interacting hub location-allocation problems to the domain of intermodal logistics. An empirical study based on a subset of US freight flows shows that intermodal logistics networks differ significantly from traditional over-the-road logistics networks in their hub locations, network structure, and their use of direct and inter-hub shipments. Furthermore, intermodal logistics networks are more sensitive to changes in service requirements and costs.     

The multistage stochastic integer load planning problem

Time-definite freight delivery common carriers, who pickup, consolidate and deliver small shipments are a key third-party logistics service provider in the supply chains. Under uncertain demands, carrier’s multistage stochastic integer load planning in the pure hub-and-spoke line-haul operations network is to determine multistage freight paths and distribute trailers over time while meeting operational restrictions, service requirements, and balancing trailer inventory at the termination of planning horizon. We developed a heuristic approach, scenario aggregation with embedded branching on the binary variables. The numerical experiments showed a proactive operations strategy with a lower operating cost than the conventionally deterministic approach.     

Supply chain micro-communities in urban areas

An increase in urban freight transport is inevitable as growing urban populations require more goods, more conveniently. A deeper understanding of the geography and trends of urban freight transport must recognise that it is the aggregate result of a complex web of supply chain interactions. To understand the trends, the behaviour of the underlying supply chains must be understood. Using Global Positioning System (GPS) traces of commercial vehicles and network theory concepts, this paper examines the characteristics of supply chain micro-communities in three urban areas in South Africa. The similarity in the structure of these micro-communities across the three, very diverse, areas suggests that the dynamics that drive supply chain interaction are not dependent on local geography. Four prominent archetypes were identified that account for more than half of the micro-communities in each area. Directionality, geographic dispersion and the balance of importance in the micro-communities are studied in the context of these archetypes. This paper presents a first puzzle piece in deducing urban freight transport patterns from supply chain interaction. Furthermore the results are an empirical benchmark that can validate theoretic models of urban supply chain interaction.     

Freight transportation demand elasticities: a geographic multimodal transportation network analysis

This paper presents direct and cross-elasticity estimates of the demands for three freight transportation modes: rail, road and inland waterways. They are computed for 10 different categories of goods with a detailed multimodal network model of Belgian freight transports. The model, which minimises the generalised cost of transportation tasks defined by O-D matrices, assigns traffic flows to the different modes, transport means and routes. Successive simulations with different relative costs permit the computation of specific arc-elasticities. In contrast with the usual methodologies, the present methodology is not based on a statistical analysis of disaggregate data on actual modal choices and transport tariffs. This is a particularly useful feature since such data are mostly not available for freight transports in Europe. Furthermore, it fully takes into account the detailed characteristics of the network, all available routes and combinations of modes, as well as the specific localisation of activities within the network. Its estimates are compared with previously published estimates, and, in particular, with Abdelwahab's results published (1998) in this journal.     

Synchromodal hinterland freight transport: Model study for the port of Rotterdam

This paper develops a model that enables comparative analysis of intermodal and synchromodal operations from economic, societal, and environmental perspectives. The model captures relevant (day-to-day and within-day) dynamics in freight transport demand and supply, flexible multimodal routing with transfers and transhipments. The capacitated schedule-based assignment algorithm operating specifically at path level allows strategic modelling and evaluation accounting for the freight transport system at operational level. The Rotterdam hinterland container transport case study shows that synchromodal system is likely to improve transport service level, capacity utilization, and modal shift, but not to reduce delivery costs.     

A supply chain-transport supernetwork equilibrium model with the behaviour of freight carriers

This paper presents a supernetwork equilibrium model integrating supply chain networks with a transport network, namely, a supply chain-transport supernetwork equilibrium model. The model takes into account the behaviour of freight carriers and transport network users to endogenously determine the transport costs generated in the supply chain networks. The interaction between transport network and supply chain networks can also be examined. Results of the numerical tests reveal that the improvement of transport network could enhance the efficiency of supply chain networks. The paper makes contributions to modelling of supply chain networks as well as to that of transport networks.     

Adding a freight network to a national interstate input–output model: a TransNIEMO application for California

The state of the nation’s infrastructure is the subject of widespread discussion and comment because it is thought to include many deteriorating and unsafe bridges. Ever since the terrorist attacks of 9/11, there has been increasing concern over the extent to which an attack on infrastructure could result in serious economic disruption. This research develops a model to analyze the economic consequences of an attack on a major element of the highway network. We add a freight network to a national multiregional economic impact model and make freight traffic flows endogenous. The use of a sub-national interstate model recognizes that most infrastructure planning is at the state level and most political leaders’ interest is local. We base our approach on the National Interstate Economic Model (NIEMO) and refer to an elaboration that we name Transportation network and the National Interstate Economic Model (TransNIEMO). The new model enables us to study the state-specific and industry-specific economic impacts of some significant changes in the nature of highway freight movements. We tested the model for selected freight movements in and out of California. The results are entirely plausible and encourage us to elaborate and test the model for hypothetical disruptions of freight traffic throughout the US.     

Time series forecasting of quarterly railroad grain carloadings

The participants in the grain logistics system need forecasts of railroad grain carloads. Although forecasting studies have been conducted for virtually every mode, no forecasting studies of quarterly railroad grain transportation have been published. The objectives of the paper are (1) specify a US quarterly railroad grain transportation forecasting model, and (2) empirically estimate the model. The selection of explanatory variables requires that they have a theoretical relationship to railroad grain transportation supply and/or demand, and that the data for the explanatory variables are published in quarterly frequency. However, there are relatively few potential explanatory variables that are published quarterly and those that are available appear to have weak correlation with quarterly railroad grain carloadings. The economic process generating quarterly railroad grain carloadings is quite complex and very difficult to model with regression techniques. Given this problem and the focus on short run forecasting, a time series model was employed to forecast quarterly railroad grain carloadings. An AR(4) model was estimated using the Maximum Likelihood estimation procedure for the 1987:4–1997:4 period. The actual railroad grain carloadings for this period were compared to the forecast carloadings generated by the time series model. For 92% of the 37 quarters the percentage difference between the actual and forecast values was 10% or less. Of the 9 annual observations, the per cent difference between the actual and forecast value was less than 2.6% for 8 of the 9 years. ©     

The ship routing and freight assignment problem for daily frequency operation of maritime liner shipping

To cope with excess capacity and improve service quality, maritime international liner carriers have recently adopted a new operational model known as daily frequency. In this new model, carriers provide daily pickup and delivery service to customers at major ports along the Pacific Rim. We investigate the ship routing and freight assignment problem for daily frequency operation of liner shipping. A solution procedure that incorporates a Lagrangian relaxation technique and local search was proposed. The numerical results show that Shanghai, Hong Kong and Singapore are ports that are ideal for carriers in establishing daily frequency operations along the Pacific Rim.     

Interregional trade network analysis for road freight transport in Greece

This paper suggests a flexible decision support framework for the strategic planning of a freight transport hub network in Greece. The proposed methodology treats practical aspects related to the optimal number, location and geographical covering of hubs, through the network analysis of interregional trade, based on original survey data for road freight flows during 2004–2012. The results offer insights into the hierarchical structure of the network and related investment priorities, as the hub role of a prefecture is found to be strongly influenced by high population densities and manufacturing specialization, and its location along highway corridors.     

Decomposing excess commuting: a Monte Carlo simulation approach

Excess or wasteful commuting is measured as the proportion of actual commute that is over minimum (optimal) commute when assuming that people could freely swap their homes and jobs in a city. Studies usually rely on survey data to define actual commute, and measure the optimal commute at an aggregate zonal level by Linear Programming (LP). Travel time from a survey could include reporting errors and respondents might not be representative of the areas they reside; and the derived optimal commute at an aggregate areal level is also subject to the zonal effect. Both may bias the estimate of excess commuting. Based on the 2006–2010 Census for Transportation Planning Package (CTPP) data in Baton Rouge, Louisiana, this research uses a Monte Carlo approach to simulate individual resident workers and individual jobs within census tracts, estimate commute distance and time from journey-to-work trips, and define the optimal commute based on simulated individual locations. Findings indicate that both reporting errors and the use of aggregate zonal data contribute to miscalculation of excess commuting.     

The impacts on freight train operational performance of new rail infrastructure to segregate passenger and freight traffic

Rail freight has an important role to play in improving the resource efficiency and sustainability of freight transport within the supply chain. The British rail network has seen considerable growth of both freight and passenger activity in the last 20 years, leading to concerns about its capacity to absorb continued growth. A number of infrastructure initiatives focused on increasing capacity and reducing conflicts have been implemented. This includes the North Doncaster Chord, opened in June 2014 primarily to provide a more direct route from the port of Immingham to the major Aire Valley power stations (i.e. Drax, Eggborough and Ferrybridge).The paper analyses the freight impacts of the new chord, focusing on three key operational measures (i.e. train routing, scheduled journey times and train punctuality) during 10-week survey periods before and after the opening of the chord. The analysis is based on real-time data relating to coal and biomass trains operating between Immingham and the three power stations. This is a novel approach as the data have been made publicly available only recently, allowing a detailed investigation of the flows on this corridor at a highly disaggregated level. The use of this empirical method to assess the detailed rail freight operational impacts is an important element in the process of evaluating the effects of network enhancement. The results demonstrate improvements in each of the three operational measures, but also reveal a situation considerably more complex than that suggested by the published material relating to the justification for this new infrastructure.     

Estimating annual average daily traffic and transport emissions for a national road network: A bottom-up methodology for both nationally-aggregated and spatially-disaggregated results

The regular and robust collection of traffic data for the entire road network in a given country will usually require high-cost investment in traffic surveys and automated traffic counters. This paper provides an alternative and low-cost approach for estimating annual average daily traffic values (AADTs) and the associated transport emissions for all road segments in a country. This is achieved by parsing and processing commonly available information from existing geographical data, census data, traffic data and vehicle fleet data. Ceteris paribus, we find that our annual average daily traffic estimation based on a neural network performs better than traditional regression models, and that the outcomes of our aggregated bottom-up road segment emission estimations are close to the outcomes from top-down models based on total energy consumption in transport. The developed approach can serve as a means of reliably estimating and verifying national road transport emissions, as well as offering a robust means of spatially analysing road transport activity and emissions, so as to support spatial emission inventory compilations, compliance with international environmental agreements, transport simulation modelling and transport planning.     

The application of inventory transshipment modeling to air cargo revenue management

This paper applies an inventory transshipment modeling approach to investigate the air cargo revenue management problem for an airline operating in a two-segment network. Building upon an extension of the classic two-location inventory transshipment model, we develop a framework to optimize an airline’s cargo overbooking decisions in a two-segment network setting. We find consistent evidence indicating that network-based global optimization always leads to greater expected profits than does local (i.e., market by market) optimization. Further, the magnitude of profit improvement is found to be most significant when local shipments have a relatively higher freight yield compared to flow-through shipments. Finally, our results indicate that global optimization contributes to greater profit improvement as offloading penalty costs become higher.     

应用改进重力模型法预测铁路行包OD运量的研究

对铁路行包OD运量的预测提出一种基于重力模型的改进方法。针对不完整的OD调查数据,运用综合阻抗的概念,首先在样本值的范围内进行模型标定,然后扩大样本值,运用标定好的重力模型重新预测并调整,最后得到完整的OD数据。实证结果表明,采用改进的重力模型比传统的重力模型预测结果更接近实际,可用于铁路行包运输OD运量预测。     

A multilayer model to simulate cruising for parking in urban areas

In this paper we propose an assignment model on urban networks to simulate parking choices; this model is able to simulate the impact of cruising for parking on traffic congestion. For simulating parking choice and estimating the impact of cruising on road congestion we propose a multi-layer network supply model, where each layer simulates a trip phase (on-car trip between the origin and destination zone, cruising for parking at destination zone and walking egress trip). In this model the cruising time is explicitly simulated on the network. The proposed model is tested on a trial network and on a real-scale network; numerical tests highlighted that the proposed model is able to simulate user parking choice behaviour and the impact of cruising for parking upon road congestion, particularly when the average parking saturation degrees exceed 0.7.