基于客户满意度的货运动车组开行方案研究

高铁货运逐渐兴起,本文对货运动车组开行方案优化进行了研究。针对高铁运输安全、快捷、运输成本较低等特性,提出以货运动车组及客货混编动车组为主,客运动车组捎带运输为补充的开行模式,结合运输需求、线路通过能力等限条件,以运输成本最小和货主满意度最大为目标,建立多目标综合优化模型,运用线性加权组合法,以lingo软件为依托进行求解。通过算例给出具体开行方案,并对同一运输区间各种运输方式的单位成本及用时进行对比分析。结果表明,相对于传统运输方式,高铁货运综合运输成本较低,用时更短,能够兼顾运输企业与货主的双重要求;所建模型优化效果明显,可为未来货运动车组的开行提供参考。     

Rail-truck multimodal freight collaboration: a statistical analysis of freight-shipper perspectives

Due to the effects of congestion, capacity reduction of truck-freight carriers, growing freight transportation demand, and increasing social and environmental concerns, there is a critical need for freight shippers to improve shipping quality and reduce transportation costs. Rail-truck multimodal freight collaboration can potentially address this need. In this study, we explore freight-shipper perspectives relating to the factors that may foster or impede their usage of rail-truck multimodal freight collaboration services, and the correlations of their operational and behavioral characteristics with these factors. The study provides insights to rail and truck carriers on collaboration mechanisms that can address the needs of freight shippers, including adopting synergistic technology to improve in-transit visibility, accommodating non-containerized cargo, improving the transshipment process, designing service quality control strategies, and constructing investment and revenue-sharing plans.     

Evaluating the public investment mix in US freight transportation infrastructure

This research empirically evaluates the public sector investment in the US freight transportation infrastructure. In particular, the infrastructures to support the two most comparable modes of freight transportation – highway and intermodal rail – are examined as alternatives for public fund allocation. Indicators for public sector transportation infrastructure investment mix are established based on financial analysis of both private and social costs and benefits, as well as the propensity of freight shippers to utilize such infrastructures. The research results in recommendations for the aggregate allocation of public funds in the US based on these indicators. We find that approximately a quarter of truck freight could be handled at a 25% lower cost if rail infrastructure to support it existed. Because an additional 80% reduction in social costs could be achieved through this modal conversion, the public sector is a critical participant in creating a more efficient transportation infrastructure.     

Challenges raised by freight for the operations planning of a shared-use rail network. A French perspective

Operating rail infrastructures that are shared among different uses is complex. In Western Europe, the predominance of passenger traffic over freight has traditionally led to thorough scheduling of capacity use, with an increasing tendency to anticipate through the design of regular-interval timetables. The paper discusses the specific challenges posed by fitting freight into the timetabling process for a mixed-use rail network, based on current French experience. The analysis is carried out from the perspective of the infrastructure manager. It is mainly supported by the results of a series of about 30 interviews, carried out in 2012 and 2013 with the parties involved in the timetabling process. The paper provides a comprehensive understanding of the process in terms of organization, rules and practices, with an emphasis on the characteristics of freight traffic compared with passenger traffic. The author highlights three key management issues for the French infrastructure manager when dealing with freight: (1) the uncertainty surrounding the mid-long term development of the rail freight market at the national level; (2) the heterogeneity resulting from the diversity of commodities, convoys and profiles and behaviors of the capacity applicants; (3) the volatility of some freight traffic resulting in a great amount of activity in the later stages of the timetabling process. If uncertainty about the future appears to be a highly sensitive issue in the French context, heterogeneity and volatility of freight traffic can be perceived as management challenges that may be experienced, to a greater or lesser degree, on other rail networks.     

Stochastic freight flow patterns: implications for fleet optimization

Trucking, rail and other types of transportation networks share the common feature of moving equipment and crews between spatially separated terminals to accommodate the transportation of goods or people. This paper develops measures for temporal and spatial imbalances in freight flows, and applies these measures to a major trucking network. Fundamentally, the randomness inherent to a system of terminals is mitigated by pooling freight flows among terminal groups, and by pooling freight flows over many time periods. In the terminal network that we examined, long-run freight imbalances ensure that empty equipment movements must equal or exceed 13.3% of loaded movements at individual terminals and 8.2% of loaded movements at terminal groups. Due to short-run freight imbalances, the number of empty movements could increase by about 50% over the long-run average; greater increases would occur if equipment flows must be balanced on each travel lane. ©     

Freight transportation demand: A survey of recent econometric studies

This paper surveys econometric studies of freight transportation demand which have been published since the mid-1970s. It describes the variables, data sources, and estimation procedures utilized by the studies. In addition, it summarizes their statistical results. The studies included in this survey typically accounted for freight rates and service characteristics (e.g., transit time and reliability). Data sources often varied across the studies.Based on the data they utilized, the surveyed studies are classified as either aggregate or disaggregate. The data in the aggregate studies consist of information on total flows by modes at the regional or national level, while the data in the disaggregate studies pertain to individual shipments. The earlier aggregate studies estimated linear logit models. It has been pointed out that when they are estimated on aggregate data these models are subject to certain shortcomings. To avoid these shortcomings, more recent aggregate studies have estimated flexible forms such as translog functions. The disaggregate studies surveyed in this paper used either logit or probit models.Statistical results often varied with the commodities analyzed, making it somewhat difficult to generalize the findings of the different studies. One finding common to several studies is that freight rates have a significant impact on shipment decisions. This paper discusses certain theoretical and empirical limitations of the surveyed studies. It also offers suggestions for future research in freight transport demand. Freight demand models can be used to examine various effects of the recent deregulation in freight transportation.     

Assessing the energy and greenhouse gas emissions mitigation effectiveness of potential US modal freight policies

This paper estimates the total embodied energy and emissions modal freight requirements across the supply chain for each of over 400 sectors using Bureau of Transportation Statistics Commodity Flow Survey data and Bureau of Economic Analysis economic input-output tables for 2002. Across all sectors, direct domestic truck and rail transportation are similar in magnitude for embodied freight transportation of goods and services in terms of ton-km. However, the sectors differ significantly in energy consumption, greenhouse gas emissions, and costs per ton-km. Recent pressure to reduce energy consumption and emissions has motivated a search for more efficient freight mode choices. One solution would be to shift freight transportation away from modes that require more energy and emit more (e.g., truck) to modes that consume and emit less (e.g., rail and water).Our results show there are no individual sectors for which targeting changes would significantly decrease the total freight transportation energy and emissions, therefore we have also looked at the prospect of policies encouraging many sectors to shift modes. There are four scenarios analyzed: (1) shifting all truck to rail, shifting top 20% sector mode choice, (2) based on their emissions, (3) based on a multi-attribute analysis, and (4) increasing truck efficiency (e.g., mpg). Increasing truck efficiency by 10% results in similar energy and emissions reductions (approximately 7% for energy and 6% for emissions) as targeting the top 20% of sectors when selected based on emissions, whereas selecting the top 20% based on availability to shift from truck results in slightly less reductions of energy and emissions. Implementing policies to encourage higher efficiency in freight trucks may be a sufficient short term goal while efforts to reduce truck freight transportation through sectoral policies are implemented in the long term.     

The European freight railway system as a hub-and-spoke network

This paper addresses a hub-and-spoke network problem for railroad freight, where a central planner is to find transport routes, frequency of service, length of trains to be used, and transportation volume. Hub-and-spoke networks, often found in air freight, have not been favoured by railways in the past. Such a structure could be profitable, however, if there exist concentrated freight flows on some service links. We formulate a linear integer programming model whose objective function includes not only the typical operational cost, but also cost due to the transit time spent by freight in the network. We then develop heuristic algorithms to solve large scale instances occurring in rail freight systems in France plus Italy; Germany; and a 10-country European network. By assuming that every node is equipped with consolidation capability, we let the final solution naturally reveal potential hub locations, the impact of several of which is studied by sensitivity analysis.     

Improving the energy efficiency of freight in the United States through commodity-based analysis: justification and implementation

Efforts to reduce energy use in freight transportation usually center around “mode-based” approaches, namely improving the energy efficiency of energy intensive modes, such as truck, and shifting more freight to energy efficient modes, such as rail. In the first part of this paper we review the recent trends and future prospects for these mode-based approaches, finding that despite substantial improvement in the technological efficiency of freight modes and robust growth in the use of intermodal rail since 1980, total freight energy use across all modes in the US has grown by approximately 33%, with proportional growth in carbon emissions. In the second part of the paper we propose use of a “commodity-based” approach, in which freight energy use is disaggregated by contribution of major commodity groups, in order to support efficiency improvement at the commodity level. Two potential applications of the commodity based approach, namely (1) life cycle analysis of energy use for major commodity groups and (2) spatial analysis of freight patterns, are demonstrated using the 1993 US Commodity Flow Survey data. Results of these preliminary findings suggest that commodity groups vary widely in the ratio of energy use in production to energy use in transport, and that for many commodity groups, there may be substantial opportunities for saving energy by redistributing flow patterns. Through development of the commodity-based approach, we also identify the collaborative involvement of shippers and carriers as a key point in improving energy efficiency, since it can be used to both make the mode-based approach more effective and address new issues such as the underlying growth in tonne-km. Benefits for air quality and other transportation issues are also discussed.     

An empirical analysis of freight transport traffic modes in Brazil, 1996–2012

This paper analyses the performance of freight transportation modes in Brazil – namely air, water, rail and road – from February 1996 to August 2012 by investigating their long memory properties using fractional integration and autoregressive models on monthly tonnage data. Two important features are analysed: the degree of dependence of transportation traffic across time and its seasonal structure over the period. Furthermore, the stability of parameters across the sample period is investigated, incorporating potential structural breaks in the data, which describe discontinuity in freight transportation traffic. Some policy implications are derived.     

Integrated modeling of high performance passenger and freight train planning on shared-use corridors in the US

This paper studies strategic level train planning for high performance passenger and freight train operations on shared-use corridors in the US. We develop a hypergraph-based, two-level approach to sequentially minimize passenger and freight costs while scheduling train services. Passenger schedule delay and freight lost demand are explicitly modeled. We explore different solution strategies and conclude that a problem-tailored linearized reformulation yields superior computational performance. Using realistic parameter values, our numerical experiments show that passenger cost due to schedule delay is comparable to in-vehicle travel time cost and rail fare. In most cases, marginal freight cost increase from scheduling more passenger trains is higher than marginal reduction in passenger schedule delay cost. The heterogeneity of train speed reduces the number of freight trains that can run on a corridor. Greater tolerance for delays could reduce lost demand and overall cost on the freight side. The approach developed in the paper could be applied to other scenarios with different parameter values.     

Investigating the market for inter-modal freight technologies

Freight carried by rail has traditionally been mainly low value bulk commodities. The market for transport of such commodities appears at best static and is forming a smaller proportion of the total demand for freight transport. There is thus an urgent need for rail operators to develop practical and cost effective inter-modal systems, which offer high quality services to consignors of consumer goods whose premises are not usually connected to the rail network. Much long-haul traffic of this type is international. In continental Europe, a number of inter-modal technologies—including swapbodies and piggyback—have long been in use. Development of similar technologies for use within the more constrained loading gauge of Great Britain, has received a great boost from the impending opening of the Channel Tunnel. The alternative technologies are discussed, before turning to ways of stimating the market for them. A large part of the paper is devoted to reporting on a computerised survey using our LASP (Leeds Adaptive Stated Preference) technique. The reason for using hypothetical Stated Preference data is the inadequate nature and extent of data on actual choice decisions, particularly in circumstances in which confidential freight rates are individually negotiated and little general merchandise goes by rail. By bringing together the results of this survey with information on costs and quality of service, the likely future market for inter-modal freight technologies is assessed. It is seen that the potential for inter-modal services within Britain is very limited, although there should be a good opportunity on the major corridor from London to Scotland through the West Midlands and the North West. When the Channel Tunnel is opened, however, the potential for services between Britain and continental Europe will be enormous, provided that an adequate quality of service can be offered.     

Fuzzy modeling approach to the rail freight car inventory problem

Techniques to improve freight car fleet use are of considerable interest to the railroad industry. In this paper, we present a fuzzy inventory control approach applied to the sizing of empty cars on a rail network. We address the problem of deciding the optimal inventory level and the optimal ordering quantity for a rail freight car fleet system in which demand and travel time are uncertain variables represented as triangular fuzzy numbers. Based on the fuzzy economic order quantity (EOQ) formula, a modified fuzzy EOQ model is set up and the optimal policy is developed using the signed distance method to defuzzify the fuzzy total cost. Computational results made for the Serbian rail network case verify the proposed model as well as the efficiency of the approach.     

Scheduling freight trains traveling on complex networks

In the US, freight railways are one of the major means to transport goods from ports to inland destinations. According to the Association of American Railroad’s study, rail companies move more than 40% of the nation’s total freight. Given the fact that the freight railway industry is already running without much excess capacity, better planning and scheduling tools are needed to effectively manage the scarce resources, in order to cope with the rapidly increasing demand for railway transportation. This research develops optimization-based approaches for scheduling of freight trains. Two mathematical formulations of the scheduling problem are first introduced. One assumes the path of each train, which is the track segments each train uses, is given and the other one relaxes this assumption. Several heuristics based on mixtures of the two formulations are proposed. The proposed algorithms are able to outperform two existing heuristics, namely a simple look-ahead greedy heuristic and a global neighborhood search algorithm, in terms of railway total train delay. For large networks, two algorithms based on the idea of decomposition are developed and are shown to significantly outperform two existing algorithms.     

New routes on old railways: increasing rail’s mode share within the constraints of the existing railway network

This paper describes an integrated methodology for identifying potential ‘quick wins’ for mode shift from road to passenger rail transport. Firstly, a procedure for analysing rail’s relative competitiveness in the market for passenger transport between large urban areas is developed and then applied to a UK case study. The purpose of such analysis is to allow the identification of flows where rail is currently relatively uncompetitive (in terms of journey time in particular) and to assess the reasons for this poor performance, so that the issues which suppress rail use may be addressed. In parallel, a framework, methodology and tool for the assessment of existing and potential capacity (trains, seats, TEUs, etc.) is developed for both passenger and freight traffic, to identify and address network constraints. An illustrative example of the use of these demand and capacity assessment tools is then presented, with the tools used to identify and evaluate flows where rail demand is suppressed by poor service quality and where spare capacity exists which would allow the passenger rail service to be improved without requiring significant investments in infrastructure. The effects of such improvements on demand are predicted, and the cost implications of operating such additional services are discussed. The analysis suggests that there may be significant potential for increasing rail’s mode share by providing additional inter-urban services where rail currently offers an inferior service.     

Rail freight efficiency and competitiveness in Australia

In 1994/95, the Australian rail freight task was approximately 100 billion tonne kilometres (btkm). This freight task included some 37 btkm for the haulage of iron ore in Western Australia, 28 btkm for coal haulage in Queensland and New South Wales and about 16 btkm for interstate rail freight. This paper mainly concerns how improvements can be made to the efficiency and competitiveness of interstate rail freight services through the upgrading of sections of mainline track that currently have severe speed‐weight restrictions. Recent improvements in rail freight efficiency are discussed, with emphasis on two indicators: average unit revenues (cents per net tonne km), and average energy efficiency (net tonne km per MJ). Rail freight efficiency is high for the Western Australia iron‐ore operations, Queensland coal operations and Adelaide‐Perth general freight operations. However, between Australia's three largest cities of Melbourne, Sydney and Brisbane, some 36% of the mainline track fails to meet basic fast freight train standards with a ruling grade of 1 in 66 and no curve radius less than 800 m. The contraints on efficient rail freight operations imposed by severe terrain, and how the effects of terrain may be reduced by improved track alignment, are discussed. Some economically warranted rail track investment measures are outlined, including those identified for a National Transport Planning Taskforce. These measures have the potential to reduce liquid fuel use by over 250 million litres a year. Factors affecting competitive neutrality between road and rail freight that are outside of the present scope of Australia's National Competition Policy are broadly considered. These factors include the extensive upgrading of the National Highway System with full Federal funding, and low levels of road cost recovery from heavy trucks operating over long distances.     

An assessment of the performance of the European long intermodal freight trains (LIFTS)

Intermodal rail/road freight transport has always been considered as a competitive alternative to its road freight counterpart in the European medium- to long-distance corridors (markets). Such consideration has been based on the increasing competitiveness of some innovative rail services and the existing and prospective performance of both modes in terms of the full social – internal or operational and external – costs. The most recent innovation of rail technologies and related services launched by some European railway companies, still at the conceptual level, is the Long Intermodal Freight Train (LIFT). This is supposed to be a block train operating in long-distance corridors (markets) with a substantial and regular freight demand.This paper develops analytical models for assessing the performance of the LIFTs, the already-operating Conventional Intermodal Freight Trains (CIFTs), and their road counterpart as well. The performance consists of the full – internal (private) and external – costs of the door-to-door delivery of loading units – containers, swap-bodies, and semi-trailers. The internal costs embrace the operational costs of the transport (rail and road) and intermodal terminal operators. The external costs include the costs of the impacts of door-to-door delivery of loading units on society and the environment. These negative externalities include noise, air pollution, traffic accidents, and congestion.The models are applied to a simplified version of intermodal and road transport system using inputs from the European freight transport sector. The aims are to compare the full costs of particular modalities in order to investigate the potential of the LIFTs as compared with the CIFTs in improving the internal efficiency of the rail freight sector and its competitiveness with respect to its road counterpart. In addition, the paper attempts to assess some effects on the potential modal shift of EU (European Union) transport policies on internalizing transport externalities.     

Intermodal and international freight network modeling

The authors describe the development and application of a single, integrated digital representation of a multimodal and transcontinental freight transportation network. The network was constructed to support the simulation of some five million origin to destination freight shipments reported as part of the 1997 United States Commodity Flow Survey. The paper focuses on the routing of the tens of thousands of intermodal freight movements reported in this survey. Routings involve different combinations of truck, rail and water transportation. Geographic information systems (GIS) technology was invaluable in the cost-effective construction and maintenance of this network and in the subsequent validation of mode sequences and route selections. However, computationally efficient routing of intermodal freight shipments was found to be most efficiently accomplished outside the GIS. Selection of appropriate intermodal routes required procedures for linking freight origins and destinations to the transportation network, procedures for modeling intermodal terminal transfers and inter-carrier interlining practices, and a procedure for generating multimodal impedance functions to reflect the relative costs of alternative, survey reported mode sequences.     

A continuous approximation model for time definite many-to-many transportation

Time definite freight transportation carriers provide very reliable scheduled services between origin and destination terminals. They seek to reduce transportation costs through consolidation of shipments at hubs, but are restricted by the high levels of service to provide less circuitous routings. This paper develops a continuous approximation model for time definite transportation from many origins to many destinations. We consider a transportation carrier serving a fixed geographic region in which demand is modeled as a continuous distribution and time definite service levels are imposed by limiting the maximum travel distance via the hub network. Analytical expressions are developed for the optimal number of hubs, hub locations, and transportation costs. Computational results for an analogous discrete demand model are presented to illustrate the behavior observed with the continuous approximation models.