A portfolio approach for optimal fleet replacement toward sustainable urban freight transportation

Recently, the use of more sustainable forms of transportation such as electric vehicles (EVs) for delivering goods and parcels to customers in urban areas has received more attention from urban planners and private stakeholders. To provide some insights toward the use of EVs, this work develops an optimization framework using portfolio theory, which takes into account the cost and the risks associated with some input parameter uncertainties, for determining an optimal combination of EVs with internal combustion engine vehicles (ICEVs) in urban freight transportation (UFT) over some planning time period. This model can assist an urban freight operator to choose the best investment strategy for introducing new vehicles into its fleet while gaining economic benefits and having positive impacts on the urban environment. When taking into account the risks that are involved, the numerical results show that EVs have the potential to compete with ICEVs in UFT.     

“一带一路”中老泰铁路运输风险评价及保费研究

随着“一带一路”设施联通建设的不断推进,作为泛亚铁路中线工程的中老泰铁路也是其中重要的一部分。为研究一带一路中老泰铁路货物运输风险以及相关保费计算,本文首先采用层次分析法得到铁路货物运输过程中存在的政治因素、气候因素、运维因素和自然力因素的风险以及不同风险因素组合的权重;其次基于N-K模型对风险进行耦合,并且结合权重计算风险耦合值,根据风险耦合值划分风险区间,不同风险区间对应的附加费率不同,最后利用保费计算公式可以得到保险费用。本文末以中老泰铁路运输水果为例,基于不同风险因素的耦合得到15个风险耦合值,并计算保费,得出不同风险下的保费结果。     

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。     

Time-dependent fuzzy random location-scheduling programming for hazardous materials transportation

The tremendous use of hazardous materials has promoted the economic development, which also brings about a growing risk causing a widespread concern. In this work, we consider a location-scheduling problem on hazardous materials transportation under the assumption that transportation risks are time-dependent fuzzy random variables. First, we formulate a scheduling optimization model and design a fuzzy random simulation based genetic algorithm to optimize the departure time and dwell times for each depot–customer pair. Then we establish an expected value model and design a modified particle swarm optimization algorithm to minimize the en route risks and site risks. Finally, numerical examples are given to illustrate the effectiveness of the proposed models and algorithms.     

Multiple criteria and fuzzy based evaluation of logistics performance for intermodal transportation

This paper presents a framework to evaluate the logistics performance of intermodal freight transportation. Fuzzy set techniques are applied to assess the logistics performance within the decision process of freight operators. Using a fuzzy‐based approach, fuzzy‐AHP is applied to assess the criteria by different judgment procedures. Consequently, fuzzy‐MCDM is used to assess operators' perception of the logistics performance via proper assignment of numerical scores. The subjective judgments for hierarchical criteria are transformed into fuzzy degrees of score. The methodology provides an alternative approach to facilitate the importance of a set of performance criteria. It can also entail use of improved corresponding parameters to develop a better freight transport system.     

Methodological aspects for modeling the environmental risk of transporting hazardous materials by road

The main objective of this paper is to establish the procedures necessary to the development of a model for the environmental risk assessment of accidents involving Transporting Hazardous Materials by Road (THMR). Quantifying the environmental risk is useful in identifying areas with a high risk of accidents, which can be later discarded as main routes; orienting efficient emergency response operations; and assessing policies aimed at reducing these risks. Taking this into consideration, this study endeavors to identify the methodological aspects make possible the assessment of the impacts that arise from accidents involving the transportation of hazardous materials by road and to implement such methodological aspects in a Geographic Information System (GIS).     

Exploring public transport sustainability with neutrosophic logic

Sustainable transportation is a significant component of overall sustainable development. Increasingly, evaluation and decision-making with respect to major complex projects (for example, transportation and land use projects), a multiple attribute perspective is taken. This paper illustrates a multiple attribute decision-making approach for selecting sustainable public transportation systems under uncertainty, that is, with partial or incomplete information represented by single-valued neutrosophic sets (SVNSs). A SVNS is a generalization of a classical set, a fuzzy set, and an intuitionistic fuzzy set. Here, SVNSs and SVNS connectives are illustrated in the context of a ‘Public Transit Sustainable Mobility Analysis Tool’ (PTSMAT) which involves a composite (multiple attribute) sustainability index. A case study of PTSMAT is provided for the UBC Corridor study in Vancouver, Canada. As expected, similar results are obtained to the original study, though the neutrosophic formalism opens a wide range of possibilities for recognition of uncertainty in sustainability assessment.     

A fuzzy method for predicting the demand for rail freight transportation

The demand for rail freight transportation is a continuously changing process over space and time and is affected by many quantitative and qualitative factors. In order to develop a more rational transport planning process to be followed by railway organizations, there is a need to accurately forecast freight demand under a dynamic and uncertain environment. In conventional linear regression analysis, the deviations between the observed and the estimated values are supposed to be due to observation errors. In this paper, taking a different perspective, these deviations are regarded as the fuzziness of the system's structure. The details of fuzzy linear regression method are put forward and discussed in the paper. Based on an analyzes of the characteristics of the rail transportation problem, the proposed model was successfully applied to a real example from China. The results of that application are also presented here.     

An agent-based framework for cooperative planning of intermodal freight transport chains

The recent development of Intelligent Transportation Systems offers the possibility of cooperative planning of multi-actor systems in a distributed framework, by enabling prompt exchange of information among actors. This paper proposes a modeling framework for cooperation in intermodal freight transport chains as multi-actor systems. In this framework, the problem of optimizing freight transportation is decomposed into a suitable set of sub-problems, each representing the operations of an actor which are connected using a negotiation scheme. A Discrete Event model is developed which optimizes the system on a rolling horizon basis to account for the dynamics of intermodal freight transport operations. This framework allows for an event driven short/medium term planning of intermodal freight transport chains. The proposed methodology is evaluated using a realistic case study, and the results are compared against the First-Come-First-Served strategy, highlighting the significance of cooperation in systems operating close to capacity.     

Measuring energy and environmental efficiency of transportation systems in China based on a parallel DEA approach

Because of China’s rapid economic development, its transportation system has become one of China’s high-energy-consumption and high-pollution-emission sectors. However, little research has been done which pays close attention to China’s transportation system, especially in terms of energy and environmental efficiency evaluation. In this paper, data envelopment analysis (DEA) is applied to measure the energy and environment performance of transportation systems in China with the goal of sustainable development. This paper treats transportation as a parallel system consisting of subsystems for passenger transportation and freight transportation, and extends a parallel DEA approach to evaluate the efficiency of each subsystem. An efficiency decomposition procedure is proposed to obtain the highest achievable subsystem efficiency. Our empirical study on 30 of mainland China’s provincial-level regions shows that most of them have a low efficiency in their transportation system and the two parallel subsystems. There are large efficiency differences between the passenger and freight transportation subsystems. In addition, unbalanced development has occurred in the three large areas of China, with the east having the highest efficiency, followed by central China and then west. Therefore, more measures should be taken to balance and coordinate the development between the three large areas and between the two subsystems within them. Our analysis approach gives data for determining effective measures.     

Impacts of information technology and urbanization on less-than-truckload freight flows in China: An analysis considering spatial effects

Understanding the relationship between socioeconomic factors and the Less-than-Truckload (LTL) freight flows is important for transportation planners and policy makers. This paper explores the impacts of information technology, urbanization on LTL freight flows by using a spatial autocorrelation model with freight flow data from a leading LTL company in China. The results show that all IT variables and urbanization variables have positive effects on freight flows. Distance, as expected, is negatively correlated with the freight flow volume. The application of the spatial autocorrelation model further shows that origin dependence, destination dependence and OD dependence are all significant, justifying the consideration of spatial interdependence. Finally, policy implications are discussed based on the estimated results. These findings shed light on the impacts of internet and urbanization on freight transportation, and contribute to the design of freight policies and the development of the LTL industry.     

Using the sustainability footprint model to assess development impacts of transportation systems

A review of the sustainability literature reveals the lack of viable frameworks and management tools that can be used to accommodate both spatial and temporal variability in how stakeholder entities meet their sustainable development goals, taking into account the fact that different entities may need to pursue different priorities and also deal with different constraints and schedules at different stages of their development. This paper presents a sustainability footprint framework and model that may be used in analyzing the impacts of transportation and other infrastructure systems on regional sustainable development. A specific application of the framework is in the quality of life contributions that transportation systems may make to communities as a function of their impacts on natural assets that contribute inputs and absorb the byproducts of development. The application is illustrated in a case study that uses data from the Atlanta and Chicago Metropolitan Areas to demonstrate how this model may be applied in real life situations. The implications of this model for transport systems research, policy and practice are discussed. The value of this framework and model lie in introducing both spatial and temporal flexibility that may enable stakeholders with widely different priorities to reach consensus on interim goals for sustainable development to ultimately attain sustainability.     

Incorporating sustainability assessment in transportation planning: an urban transportation vehicle-based approach

Environmental assessments are on the critical path for the development of land, infrastructure and transportation systems. These assessments are based on planning methods which, in turn, are subject to continuous enhancement. The substantial impacts of transportation on environment, society and economy strongly urge the incorporation of sustainability into transportation planning. Two major developments that enhance transportation sustainability are new fuels and vehicle power systems. Traditional planning ignores technology including the large differences among conventional, hybrid and alternative fuel vehicles and buses. The introduction of alternative fuel vehicles is likely to change the traditional transportation planning process because different characteristics need to be taken into account. In this study a sustainability framework is developed that enables assessment of transportation vehicle characteristics. Identified indicators are grouped in five sustainability dimensions (Environment, Technology, Energy, Economy and Users). Our methodology joins life cycle impacts and a set of quantified indicators to assess the sustainability performance of seven popular light-duty vehicles and two types of transit buses. Bus Rapid Transit receives the highest sustainability index and the pickup truck the lowest. Hybrid electric vehicles are found to have the highest sustainability index among all other passenger vehicles. A sensitivity analysis shows the proposed sustainability dimensions produce robust sustainability assessment for several weighting scenarios. The results are both technology and policy sensitive, thus useful for both short- and long-term planning.     

A carbon footprint-based closed-loop supply chain model under uncertainty with risk analysis: A case study

The management of products’ end-of-life and the recovery of used products has gained significant importance in recent years. In this paper, we address the carbon footprint-based problem that arises in a closed-loop supply chain where returned products are collected from customers. These returned products can either be disposed of or be remanufactured to be resold as new ones. Given this environment, an optimization model for a closed-loop supply chain (CLSC) in which carbon emission is expressed in terms of environmental constraints, i.e., carbon emission constraints, is developed. These constraints aim to limit the carbon emission per unit of product supplied with different transportation modes. Here, we design a closed-loop network where capacity limits, single-item management and uncertainty on product demands and returns are considered. First, fuzzy mathematical programming is introduced for uncertain modeling. Then, the statistical approach to the possibility to synthesize fuzzy information is utilized. Therefore, using a defined possibilistic mean and variance, we transform the proposed fuzzy mathematical model into a crisp form to facilitate efficient computation and analysis. Finally, the risk caused by violating the estimated resource constraints is analyzed so that decision makers (DMs) can trade off between the expected cost savings and the expected risk. We utilize data from a company located in Iran.     

Dynamic charging infrastructure deployment for plug-in hybrid electric trucks

Inspired by the rapid development of charging-while-driving (CWD) technology, plans are ongoing in government agencies worldwide for the development of electrified road freight transportation systems through the deployment of dynamic charging lanes. This en route method for the charging of plug-in hybrid electric trucks is expected to supplement the more conventional charging technique, thus enabling significant reduction in fossil fuel consumption and pollutant emission from road freight transportation. In this study, we investigated the optimal deployment of dynamic charging lanes for plug-in hybrid electric trucks. First, we developed a multi-class multi-criteria user equilibrium model of the route choice behaviors of truck and passenger car drivers and the resultant equilibrium flow distributions. Considering that the developed user equilibrium model may have non-unique flow distributions, a robust deployment of dynamic charging lanes that optimizes the system performance under the worst-case flow distributions was targeted. The problem was formulated as a generalized semi-infinite min-max program, and a heuristic algorithm for solving it was proposed. This paper includes numerical examples that were used to demonstrate the application of the developed models and solution algorithms.     

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.     

Estimating economic losses of industry clusters due to port disruptions

Seaport operations are highly important for industries which rely heavily on imports and exports. A reliable evaluation of port risks is essential to govern the normal running of seaborne transportation and thus the industrial economies. The occurrence of a breakdown in the trade facilitators, such as ports, will disrupt the smooth flow of supply chains for the industries. The estimation of the economic loss for an industry when a port gets disrupted is a challenging task as the relationship between the port and industry clusters is complex. This study aims to develop a systematic framework for performing economic loss estimation of industry clusters due to port disruptions. The whole risk assessment is split into three stages focusing on the establishment of a network flow model, economic estimations and evaluating risk mitigation strategies. The proposed idea is demonstrated by a case study on Shenzhen port and its related manufacturing industries. A dynamic inventory control strategy used by manufacturers is found to be beneficial for mitigating port disruption risks.     

A model of managers’ preferences for location of freight facilities

The paper reviews the need for a better understanding of the factors which affect the location of freight facilities, such as depots, terminals, freight forwarding centres, distribution centres, etc. The development of an Elimination by Aspects (EBA) model to analyse such location decisions by the managers of freight firms is described. The results are shown to be comparable (perhaps even superior to) those obtained with a logit model. Conclusions are drawn with respect to both the use of the EBA model to analyse freight facility location preference, and the factors which affect such preference. Five factors were found to be significant: closeness to existing customers, closeness to arterial roads, availability of suitable sites, cost of truck fleet operation, and closeness to labor.     

Transportation policy analysis with a geographic information system: The virtual network of freight transportation in Europe

This paper presents a multi-modal freight transportation model based on a digitized geographic network. A systematic analysis and decomposition of all the transport operations i.e. moving, loading and unloading, transshipping and transiting, leads to the development of a virtual network where each virtual link corresponds to a specific operation, and all transportation modes and means are inter-linked. Software, called NODUS, automatically generates the virtual network so that the model can be conveniently applied to large networks. The analytical structure of the links notation makes it easy to attach specific cost functions to each virtual link. The model is applied to the trans-European freight network of roads, railways and inland waterways for the transportation of wood. Cost functions are built up for each operation by each mode/means combination. A detailed point-to-point origin-destination matrix, calibrated on Eurostat statistics, is generated by a Monte-Carlo technique. Then, the total transportation cost is minimized with respect to the choices of routes, modes and means. This provides estimations of transportation services demands as well as modal splits, to the extent that the two hypotheses of demand based on generalized cost minimization and market contestability are accepted. A sensitivity analysis on the relative road cost is made, which provides measures of arc-elasticities.     

Comparison of road freight transport trends in Europe. Coupling and decoupling factors from an Input–Output structural decomposition analysis

Decoupling road freight transport from economic growth has been acknowledged by the European Union as a key means to improving sustainability. It is therefore important to identify both the coupling and decoupling drivers of road freight transport demand in order to determine possible factors that may contribute to reduce road transport in the future without curbing economic development. This research proposes an Input–Output (IO) structural decomposition analysis (SDA) to explain road freight transport in terms of a set of key factors that have strongly influenced road freight demand in recent decades in European countries—such as economic growth, economic structure and the evolution of road transport intensity (including improvements in both supply and transport systems). This methodological approach allows us to quantify and compare their contribution in different European countries to either increase or decrease road freight transport demand. The empirical basis for this analysis is a dataset of nine European countries which have IO tables and road transport data available from 2000 to 2007, comprising data on domestic production, imports and exports as well as tonne-kms for 11 types of commodity classes. The results show that, as a whole, aggregate road transport demand has grown—driven mainly by economic activity—but this growth has been strongly curbed in some countries by changes in road freight transport intensity and moderately by the dematerialization of the economy. International transport has been also proven to be a key factor driving road freight transport volumes. Moreover, the increased penetration of foreign operators in national haulage markets appears to have reinforced the final decoupling levels observed in some cases.