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。     

External costs of the Belgian interurban freight traffic: a network analysis of their internalisation

The strong expansion of freight road transports throughout Europe is an important source of congestion and pollution, as well as a cause of many accidents. To solve this problem will require the conjunction of many different remedies. One element of solution would be the promotion and substitution of transportation modes with less negative effects. This paper is focused on this solution. It presents some results obtained from a detailed GIS modelling of the Belgian multimodal freight transport network inserted within the overall trans-European network. It outlines the results of a simulation of the flows over the Belgian network in 1995 which allows to estimate some of the costs of several external effects of freight transports: the costs of pollution, congestion, accidents, noise and road damages. This paper provides also the simulated impacts on modal choice of a marginal external cost internalisation, and an estimation of the corresponding external cost savings.     

Transportation serviceability analysis for metropolitan commuting corridors based on modal choice modeling

Major commuting corridors in metropolitan areas generally comprise multiple transportation modes for commuters, such as transit (subways or buses), private vehicles, or park-and-ride combinations. During the morning peak hour, the commuters would choose one of the available transportation modes to travel through the corridors from rural/suburban living areas to urban working areas. This paper introduces a concept of transportation serviceability to evaluate a transportation mode’s service status in a specific link, route, road, or network during a certain period. The serviceability can be measured by the possibility that travelers choose a specific type of transportation service at a certain travel cost. The commuters’ modal-choice possibilities are calculated using a stochastic equilibrium model based on general travel cost. The modeling results illustrate how transportation serviceability is influenced by background traffic flow in a corridor, value of comfort for railway mode, and parking fee distribution.     

Network design: selection and design of links and facility location

In this paper we introduce new network design problems. A network of potential links is given. Each link can be either constructed or not at a given cost. Also, each constructed link can be constructed either as a one-way or two-way link. The objective is to minimize the total construction and transportation costs. Two different transportation costs are considered: (i) traffic is generated between any pair of nodes and the transportation cost is the total cost for the users and (ii) demand for service is generated at each node and a facility is to be located on a node to satisfy the demand. The transportation cost in this case is the total cost for a round trip from the facility to each node and back. We will consider two options in regard to the links between nodes. They can either be two-way only, or mixed, with both two-way and one-way (in either direction) allowed. When these options are combined with the two objective functions, four basic problems are created. These problems are solved by a descent algorithm, simulated annealing, tabu search, and a genetic algorithm. Extensive computational results are presented.     

Positive impact of distribution centres on the environment

The transport sector in general, and trucks in particular, generates a significant amount of emissions in Australia. It appears the trend will escalate unless different measures are taken to reduce the reliance of freight transport on trucks. This paper discusses the benefits of distribution centres as a means to reduce road congestion, increase safety, protect the environment by reducing atmospheric pollution and improve freight distribution. It also provides the effective use of the existing rail network and its infrastructure and improves the lead-time as well as lowering the cost of transportation of cargo. It also investigates the positive impact of distribution centres located near to manufacturing and farming production units. A simulation model has been developed and used to help determine the amount of atmospheric pollution produced by two modes of land transport, rail and road, for the movement of containers between port and destination. Results derived from the model provide evidence about a preferred land-transport regime. The paper has two sections: (1) the role of distribution centres in the chain of transport and (2) the impact of distribution centres on the environment. The first section investigates the feasibility of the implementation of distribution centres in the State of Victoria with respect to rail line capacity and location allocation. The second section presents an additional simulation model that investigates the role of a distribution centre in relation to the amount of atmospheric pollution produced by rail and road, while containers are carried between port and destination.     

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.     

Impacts of information technology on personal travel and commercial vehicle operations: research challenges and opportunities

Travel, like many other aspects of daily life is being transformed by the information technology (IT) revolution. Accessibility can no longer be measured only in terms of travel time, distance or generalized travel cost. IT gives people virtual accessibility to a rapidly growing range of activities. E-commerce has become a catalyst for structural changes in the freight transportation industry and is changing where freight moves, the size of typical shipments and the time within which goods must be delivered. In this paper, we explore some of the potential effects of IT on transportation, both personal and freight.     

The design of capacitated intermodal hub networks with different vehicle types

In this study, we allow using alternative transportation modes and different types of vehicles in the hub networks to be designed. The aim of the problem is to determine the locations and capacities of hubs, which transportation modes to serve at hubs, allocation of non-hub nodes to hubs, and the number of vehicles of each type to operate on the hub network to route the demand between origin-destination pairs with minimum total cost. Total cost includes fixed costs of establishing hubs with different capacities, purchasing and operational costs of vehicles, transportation costs, and material handling costs. A mixed-integer programming model is developed and a variable neighborhood search algorithm is proposed for the solution of this problem. The heuristic algorithm is tested on instances from the Turkish network and CAB data set. Extensive computational analyzes are conducted in order to observe the effects of changes in various problem parameters on the resulting hub networks.     

A network‐based model for estimating the market share of a new high‐speed rail system

This paper presents a novel application of static traffic assignment methods, but with a variable time value, for estimating the market share of high‐speed rail (HSR) in the northwest–southeast (NW–SE) corridor of Korea currently served by air, conventional rail and highway modes. The proposed model employs a time–space network structure to capture the interrelations among competing transportation modes, and to reflect their supply‐ and demand‐side constraints as well as interactions through properly formulated link‐node structures. The embedded cost function for each network link offers the flexibility for incorporating all associated factors, such as travel time and fare, in the model computation, and enables the use of a distribution rather than a constant to represent the time–value variation among all transportation mode users. To capture the value‐of‐time (VOT) of tripmakers along the target corridor realistically, this study has developed a calibration method with aggregate demand information and key system performance data from the NW–SE corridor.     

A green intermodal service network design problem with travel time uncertainty

In a more and more competitive and global world, freight transports have to overcome increasingly long distances while at the same time becoming more reliable. In addition, a raising awareness of the need for environmentally friendly solutions increases the importance of transportation modes other than road. Intermodal transportation, in that regard, allows for the combination of different modes in order to exploit their individual advantages. Intermodal transportation networks offer flexible, robust and environmentally friendly alternatives to transport high volumes of goods over long distances. In order to reflect these advantages, it is the challenge to develop models which both represent multiple modes and their characteristics (e.g., fixed-time schedules and routes) as well as the transhipment between these transportation modes. In this paper, we introduce a Green Intermodal Service Network Design Problem with Travel Time Uncertainty (GISND-TTU) for combined offline intermodal routing decisions of multiple commodities. The proposed stochastic approach allows for the generation of robust transportation plans according to different objectives (i.e., cost, time and greenhouse gas (GHG) emissions) by considering uncertainties in travel times as well as demands with the help of the sample average approximation method. The proposed methodology is applied to a real-world network, which shows the advantages of stochasticity in achieving robust transportation plans.     

Generation of logistics networks in freight transportation models

This article analyzes the concept of logistics networks in the context of behavioral freight transport modeling. Starting from the basic definition of networks, the different perceptions of networks in transportation science and logistics are worked out. The micro?Cmacro gap, as a main challenge in freight transport modeling, is explained by the existence of logistics networks on a meso level. A taxonomy of modeling methods dealing with logistics networks is defined, based on two characteristics: the changeability of networks within models (fixed, partially variable and variable networks) and the form of cost functions mapped (economies of scale, constant average cost, and diseconomies of scale). For each category, different possible modeling methods and their application in existing freight transport models are discussed. A special focus is placed on methodologies and models that map variable networks.     

Train design and routing optimization for evaluating criticality of freight railroad infrastructures

Freight transportation by railroads is an integral part of the U.S. economy. Identifying critical rail infrastructures can help stakeholders prioritize protection initiatives or add necessary redundancy to maximize rail network resiliency. The criticality of an infrastructure element, link or yard, is based on the increased cost (delay) incurred when that element is disrupted. An event of disruption can cause heavy congestion so that the capacity at links and yards should be considered when freight is re-routed. This paper proposes an optimization model for making-up and routing of trains in a disruptive situation to minimize the system-wide total cost, including classification time at yards and travel time along links. Train design optimization seeks to determine the optimal number of trains, their routes, and associated blocks, subject to various capacity and operational constraints at rail links and yards. An iterative heuristic algorithm is proposed to attack the computational burden for real-world networks. The solution algorithm considers the impact of volume on travel time in a congested or near-congested network. The proposed heuristics provide quality solutions with high speed, demonstrated by numerical experiments for small instances. A case study is conducted for the network of a major U.S. Class-I railroad based on publicly available data. The paper provides maps showing the criticality of infrastructure in the study area from the viewpoint of strategic planning.     

Profit-based maritime container assignment models for liner shipping networks

We propose the problem of profit-based container assignment (P-CA), in which the container shipment demand is dependent on the freight rate, similar to the “elastic demand” in the literature on urban transportation networks. The problem involves determining the optimal freight rates, the number of containers to transport and how to transport the containers in a liner shipping network to maximize the total profit. We first consider a tactical-level P-CA with known demand functions that are estimated based on historical data and formulate it as a nonlinear optimization model. The tactical-level P-CA can be used for evaluating and improving the container liner shipping network. We then address the operational-level P-CA with unknown demand functions, which aims to design a mechanism that adjusts the freight rates to maximize the profit. A theoretically convergent trial-and-error approach, and a practical trial-and-error approach, are developed. A numerical example is reported to illustrate the application of the models and approaches.     

The treatment of uncertainty in the dynamic origin–destination estimation problem using a fuzzy approach

Regardless of existing types of transportation and traffic model and their applications, the essential input to these models is travel demand, which is usually described using origin–destination (OD) matrices. Due to the high cost and time required for the direct development of such matrices, they are sometimes estimated indirectly from traffic measurements recorded from the transportation network. Based on an assumed demand profile, OD estimation problems can be categorized into static or dynamic groups. Dynamic OD demand provides valuable information on the within-day fluctuation of traffic, which can be employed to analyse congestion dissipation. In addition, OD estimates are essential inputs to dynamic traffic assignment (DTA) models. This study presents a fuzzy approach to dynamic OD estimation problems. The problems are approached using a two-level model in which demand is estimated in the upper level and the lower level performs DTA via traffic simulation. Using fuzzy rules and the fuzzy C-Mean clustering approach, the proposed method treats uncertainty in historical OD demand and observed link counts. The approach employs expert knowledge to model fitted link counts and to set boundaries for the optimization problem by defining functions in the fuzzification process. The same operation is performed on the simulation outputs, and the entire process enables different types of optimization algorithm to be employed. The Box-complex method is utilized as an optimization algorithm in the implementation of the approach. Empirical case studies are performed on two networks to evaluate the validity and accuracy of the approach. The study results for a synthetic network and a real network demonstrate the robust performance of the proposed method even when using low-quality historical demand data.     

The evaluation of transportation energy efficiency: An application of three-stage virtual frontier DEA

In this paper, transportation energy efficiency is newly defined and its inputs and outputs are obtained through literature review. Labor input, capital input and energy input are selected as the inputs, passenger turnover volume and freight turnover volume are defined as the outputs. A new model—three-stage virtual frontier DEA (three-stage virtual frontier Data Envelopment Analysis) is proposed to evaluate transportation energy efficiencies. The case of thirty Chinese PARs (provincial administrative regions) from 2003 to 2012 is applied to verify its rationality. In the three-stage virtual frontier DEA, the reference DMU (decision-making unit) set and the evaluated DMU set are two different sets so that it can distinguish the DEA efficient DMUs. And in the evaluating process, the reference DMU set remains unchanged to assure its results more reasonable than Super DEA model. The results show that transport structure and management measures have important impacts on transportation energy efficiency.     

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.     

Joint optimization of freight facility location and pavement infrastructure rehabilitation under network traffic equilibrium

Establishment of industry facilities often induces heavy vehicle traffic that exacerbates congestion and pavement deterioration in the neighboring highway network. While planning facility locations and land use developments, it is important to take into account the routing of freight vehicles, the impact on public traffic, as well as the planning of pavement rehabilitation. This paper presents an integrated facility location model that simultaneously considers traffic routing under congestion and pavement rehabilitation under deterioration. The objective is to minimize the total cost due to facility investment, transportation cost including traffic delay, and pavement life-cycle costs. Building upon analytical results on optimal pavement rehabilitation, the problem is formulated into a bi-level mixed-integer non-linear program (MINLP), with facility location, freight shipment routing and pavement rehabilitation decisions in the upper level and traffic equilibrium in the lower level. This problem is then reformulated into an equivalent single-level MINLP based on Karush–Kuhn–Tucker (KKT) conditions and approximation by piece-wise linear functions. Numerical experiments on hypothetical and empirical network examples are conducted to show performance of the proposed algorithm and to draw managerial insights.     

Emission rates of intermodal rail/road and road-only transportation in Europe: A comprehensive simulation study

Intermodal rail/road transportation combines advantages of both modes of transport and is often seen as an effective approach for reducing the environmental impact of freight transportation. This is because it is often expected that rail transportation emits less greenhouse gases than road transportation. However, the actual emissions of both modes of transport depend on various factors like vehicle type, traction type, fuel emission factors, payload utilization, slope profile or traffic conditions. Still, comprehensive experimental results for estimating emission rates from heavy and voluminous goods in large-scale transportation systems are hardly available so far. This study describes an intermodal rail/road network model that covers the majority of European countries. Using this network model, we estimate emission rates with a mesoscopic model within and between the considered countries by conducting a large-scale simulation of road-only transports and intermodal transports. We show that there are high variations of emission rates for both road-only transportation and intermodal rail/road transportation over the different transport relations in Europe. We found that intermodal routing is more eco-friendly than road-only routing for more than 90% of the simulated shipments. Again, this value varies strongly among country pairs.     

Bounded rationality and irreversible network change

A network change is said to be irreversible if the initial network equilibrium cannot be restored by revoking the change. The phenomenon of irreversible network change has been observed in reality. To model this phenomenon, we develop a day-to-day dynamic model whose fixed point is a boundedly rational user equilibrium (BRUE) flow. Our BRUE based approach to modeling irreversible network change has two advantages over other methods based on Wardrop user equilibrium (UE) or stochastic user equilibrium (SUE). First, the existence of multiple network equilibria is necessary for modeling irreversible network change. Unlike UE or SUE, the BRUE multiple equilibria do not rely on non-separable link cost functions, which makes our model applicable to real-world large-scale networks, where well-calibrated non-separable link cost functions are generally not available. Second, travelers’ boundedly rational behavior in route choice is explicitly considered in our model. The proposed model is applied to the Twin Cities network to model the flow evolution during the collapse and reopening of the I-35 W Bridge. The results show that our model can to a reasonable level reproduce the observed phenomenon of irreversible network change.     

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.