A two-phase model for dry port location with an application to the port of Dalian in China

This paper provides guidance for an optimal and reasonable dry port layout for the port of Dalian in China. We present a two-phase framework on the location of dry ports, which solves the selection of candidate inland cities and optimal dry port location choice, respectively. Fuzzy C-Means Clustering is applied to select alternative cities in the vast hinterland of the seaport of Dalian, with a view to identify evaluation factors that affect the location selection decision. A cost-minimisation linear programming solution is proposed, with the aid of a genetic algorithm, to choose the optimal location as well as capacity level among the candidate inland cities.     

Collaborative Logistics from the Perspective of Road Transportation Companies

ABSTRACT

To survive under the ever increasing competitive and global pressures to operate more efficiently, transportation companies are obliged to adopt a collaborative focus. Various types of cooperative supply chain relationships have been discussed in both professional and academic literature over the last decades. However, research on horizontal cooperation in logistics remains scarce and scattered across various research domains. Companies operating at the same level of the supply chain and performing comparable logistics functions may cooperate horizontally to increase their productivity, improve their service level and enhance their market position. In this paper, the focus is on the operational planning of horizontal cooperations between road transportation carriers. Following a scientific literature review, a distinction may be made between two operational approaches to horizontal logistics collaboration: order sharing and capacity sharing. For both research streams, a detailed overview of solution techniques proposed in literature is presented. Moreover, some interesting opportunities for future research are identified.     

Greening ports and maritime logistics: A review

This paper aims to examine the past and present research on ‘green ports and maritime logistics’ in order to identify established research streams and fertile research areas with potential for future investigations. Using rigorous bibliometric and network analysis tools, the paper completes a systemic mapping of the existing literature and identifies the key investigators, collaboration patterns, research clusters and interrelationships, and the “seminal research areas” that have provided the field with the foundational knowledge, concepts, theories, tools, and techniques. Major articles within each seminal research area are also identified. This will allow new researchers to quickly build understanding in a particular sub-field by reading these major articles. The findings obtained from the evolution of seminal research areas over time are important from both research and practice perspectives and can help the field grow in many dimensions.     

Planning for economic and environmental resilience

Climate protection will require major reductions in GHG emissions from all sectors of the economy, including the transportation sector. Slowing growth in vehicle miles traveled (VMT) will be necessary for reducing transportation GHG emissions, even with major breakthroughs in vehicle technologies and low-carbon fuels (Winkelman et al., 2009). The Center for Clean Air Policy (CCAP) supports market-based policy approaches that minimize costs and maximize benefits. Our research indicates that significant GHG reductions can be achieved through smart growth and travel efficiency measures that increase accessibility, improve travel choices and make optimum use of existing infrastructure. Moreover, we find such measures can deliver compelling economic benefits, including avoided infrastructure costs, leveraged private investment, increased local tax revenues and consumer vehicle ownership and operating cost savings (Winkelman et al., 2009).As a society, what we build – where and how – has a tremendous impact on our carbon footprint, from building design to transportation infrastructure and land-use patterns. The empirical and modeling evidence is clear – people drive less in locations with efficient land use patterns, high quality travel choices and reinforcing policies and incentives (Ewing et al., 2008). It is also clear that there is growing and unmet market demand for walkable communities, reinforced by demographic shifts and higher fuel prices (Leinberger, 2006, Nelson, 2007). Transportation policy in the United States must rise to meet this demand for more travel choices and more livable communities.The academic, ideological and political debates about the level of GHG reductions and penetration rates that can or should be achieved via smart growth and pricing on the one hand, or measures such as ‘eco-driving’ and signal optimization on the other, have served their purpose: we know which policies are ‘directionally correct’ – policies that reduce GHG emissions even though we may not know the scope of those reductions. Now is the time to implement directionally correct policies, assess what works best where, and refine policy based on the results. It is a framework that CCAP calls “Do. Measure. Learn.”The Federal government is poised to spend $500 billion on transportation (Committee on Transportation and Infrastructure, 2009). CCAP encourages Congress to “Ask the Climate Question” – will our transportation investments help reduce GHG emissions or exacerbate the problem? Will they help increase our resilience to climate change impacts or increase our vulnerability? And, while we’re at it, will our investment foster energy security, livable communities and a vibrant economy? Federal transportation and climate policies should empower communities to implement locally-determined travel efficiency solutions by providing appropriate funding, tools and technical support.     

Stochastic dynamic itinerary interception refueling location problem with queue delay for electric taxi charging stations

A new facility location model and a solution algorithm are proposed that feature (1) itinerary-interception instead of flow-interception; (2) stochastic demand as dynamic service requests; and (3) queueing delay. These features are essential to analyze battery-powered electric shared-ride taxis operating in a connected, centralized dispatch manner. The model and solution method are based on a bi-level, simulation–optimization framework that combines an upper level multiple-server allocation model with queueing delay and a lower level dispatch simulation based on earlier work by Jung and Jayakrishnan. The solution algorithm is tested on a fleet of 600 shared-taxis in Seoul, Korea, spanning 603 km², a budget of 100 charging stations, and up to 22 candidate charging locations, against a benchmark “naïve” genetic algorithm that does not consider cyclic interactions between the taxi charging demand and the charger allocations with queue delay. Results show not only that the proposed model is capable of locating charging stations with stochastic dynamic itinerary-interception and queue delay, but that the bi-level solution method improves upon the benchmark algorithm in terms of realized queue delay, total time of operation of taxi service, and service request rejections. Furthermore, we show how much additional benefit in level of service is possible in the upper-bound scenario when the number of charging stations is unbounded.     

Evaluating household residential preferences for walkability and accessibility across three U.S. regions

Accessibility has been established as a major planning goal in recent years. However, little knowledge exists regarding how individuals value walkability, transit accessibility, and auto accessibility differently when deciding where to live. To fill this knowledge gap, this study conducts residential location choice modeling across three U.S. regions—Atlanta, Puget Sound, and Southeast Michigan. I find that, overall, all three types of accessibility are important determinants of residential location choice. Transit accessibility has a statistically significant positive influence on residential location choice across all three regions. On auto accessibility, results show that commute time by auto has the greatest influence on residential location choice among all independent variables, but auto accessibility to nonwork destinations appears to be inconsequential. Moreover, walkability is found to be a key determinant of residential location choice in the Puget Sound region but not the other two regions. I argue that these regional differences result from a lack of choice among Atlanta and Southeast Michigan residents, that is, a undersupply of walkable neighborhoods inhibits households in the two regions from living in such neighborhoods. This finding suggests the need for cities and regions to promote pedestrian-oriented development in order to broaden residential choice. The results further imply that, due to housing-supply constraints, households often have to live in a neighborhood with a level of accessibility lower than what they prefer. Transportation and land-use planners should address this “residential dissonance” when applying residential location choice models to predict land-use growth patterns.     

Optimal starting location of an HOV lane for a linear monocentric urban area

This paper analyzes the optimal starting location of a high-occupancy-vehicle (HOV) lane for a linear monocentric urban area. Both travel time and carpooling costs are taken into account. The research proposes an analytical framework for the case with a continuum demand distribution along a highway corridor. The objective is assumed to maximize social welfare of the transportation system, which is the difference between the total user benefit and travel cost. Numerical analysis via simulation experiments was conducted to seek the existence of an optimal solution. Based on the results of a sensitivity analysis, we find a specific relationship between the carpooling cost and the optimal design of the starting point of an HOV lane.     

新时期“服务区+旅游”发展模式及功能定位

为了满足人们对高速公路服务区功能多元化需求,支撑高速公路服务区可持续发展,本文探索了“服务区+旅游”概念,从地理位置、自然资源、文化资源、产业资源、车流量多维度分析了“服务区+旅游”特征,研究了新时期背景下“服务区+旅游”典型融合模式和单体服务区+旅游融合发展功能定位,并以莆炎高速(福州段)梧桐服务区为开展实证研究。结果表明:1)服务区+旅游典型模式宜划分为综合型、自然资源型、人文资源型、基本型四种;2)单体服务区+旅游融合发展应从区位因素、资源因素、经济因素进行功能定位;3)通过实践应用,福建莆炎高速梧桐服务区功能定位为综合型服务区。研究成果可以强化服务区社会效益,适当提高其经济效益,支撑高速公路服务区的可持续发展。     

The longer and heavier vehicle debate: A review of empirical evidence from Germany

This paper aims to evaluate the likely effects of the adoption of Longer Heavier Vehicles (LHVs) from the perspective of logistics service providers (LSPs). The research consists of six case studies and a survey of companies which were involved LHV trials in Germany. Wider introduction of LHVs is being increasingly demanded so that road freight transport can better serve and support modern supply chains whilst achieving the desired eco-efficiency advancements. Available literature on LHVs puts a particular emphasis on five factors that need to be included in the assessment of their impact: energy efficiency, CO₂ emissions, costs, safety and infrastructure. The research provides an original and innovative empirical study refining and validating the current conceptual framework for assessing LHVs demonstrating it is a valuable tool and providing evidence that the vast majority of companies participating in our study, regardless of their size, were interested in the adoption of LHVs. However, it should be noted that a key limitation of the research is that by focusing on a single country case, the nature and scale of the findings may not reflect practice in other countries and sectors. There is also a need to examine the long-term sustainability of the improvements made.     

Dynamic routing-and-inventory problems: a review

The paper presents a review of the available literature on a class of problems denoted as dynamic routing-and-inventory (DRAl) problems. They are characterized by the simultaneous relevance of routing and of inventory issues in a dynamic environment, within the framework of distribution logistics. A classification scheme is first proposed for these problems. Then the results obtained in this area are summarized. Finally, the papers available in the literature are clustered and discussed according to the proposed scheme.     

Incorporating Logistics in Freight Transport Demand Models: State-of-the-Art and Research Opportunities

Freight transport demand is a demand derived from all the activities needed to move goods between locations of production to locations of consumption, including trade, logistics and transportation. A good representation of logistics in freight transport demand models allows us to predict the effects of changes in logistics systems on future transport flows. As such it provides better estimations of the costs of interaction and allows to predict changes in spatial patterns of freight transport flows more accurately. In recent years, the attention for freight modelling has been growing and new research work has appeared aimed at incorporating logistics in freight models. In this paper we review the state of the art in the representation of logistics considerations in freight transport demand models. Our focus is on the service and cost drivers of changes in logistics networks and how these affect freight transport. Our review proceeds along a conceptual framework for modelling that goes beyond the conventional 4-step modelling approach. We identify promising areas for freight modelling that have an integrative function within this framework, such as spatial computable general equilibrium models, supply chain choice models and hypernetwork models.     

Forecasting current and next trip purpose with social media data and Google Places

Trip purpose is crucial to travel behavior modeling and travel demand estimation for transportation planning and investment decisions. However, the spatial-temporal complexity of human activities makes the prediction of trip purpose a challenging problem. This research, an extension of work by Ermagun et al. (2017) and Meng et al. (2017), addresses the problem of predicting both current and next trip purposes with both Google Places and social media data. First, this paper implements a new approach to match points of interest (POIs) from the Google Places API with historical Twitter data. Therefore, the popularity of each POI can be obtained. Additionally, a Bayesian neural network (BNN) is employed to model the trip dependence on each individual’s daily trip chain and infer the trip purpose. Compared with traditional models, it is found that Google Places and Twitter information can greatly improve the overall accuracy of prediction for certain activities, including “EatOut”, “Personal”, “Recreation” and “Shopping”, but not for “Education” and “Transportation”. In addition, trip duration is found to be an important factor in inferring activity/trip purposes. Further, to address the computational challenge in the BNN, an elastic net is implemented for feature selection before the classification task. Our research can lead to three types of possible applications: activity-based travel demand modeling, survey labeling assistance, and online recommendations.     

Selection Criteria of Transportation Mode: A Case Study in Four Finnish Industry Sectors

Abstract

This paper takes a closer look at the very basics of logistics and it analyses the selection criteria of transportation services from the industrial point of view as the main research problem. It also tries to establish a better understanding of which industrial sectors are using which mode of logistics services and why. According to the analysis, the high value and especially high price/kg ratio of products, short life cycles and worldwide markets are typical reasons to use rapid modes of transport. The high price/kg ratio of products and the short life cycles, for example in the electronics industry, cause high price erosion and support selecting transport based on speed, as proportional transport costs remain small, even when using expensive transportation modes. Based on the results, some of the future logistics needs were identified, and the aim is to help logistics service providers offer the exact services needed, providing better competitiveness for Finnish shipping companies operating in global markets. Logistics service providers are, for example, expected to have more powerful supply chain management capabilities than a single‐service provider can typically offer. Additionally, logistics service providers should have compatible operating systems with different parties of various supply chains to enable deliveries to different customer groups according to their industry’s required speed.     

The location of public logistic centers: an expanded capacity-limited fixed cost location-allocation modeling approach

The location problem considered in this paper concerns the optimal number, size, and location of public logistic centers. To solve this problem, a mathematical model is developed based on an expanded capacity-limited fixed cost location-allocation model of a network incorporating handling costs and the costs of the temporary storage of cargo in the logistic center. The effectiveness of the proposed approach is evaluated with a numerical example of locating public logistic centers of international importance in the Republic of Serbia, based on two scenarios regarding the future development of import cargo flows into the Republic to the year 2020.     

The private and social cost efficiency of port hinterland container distribution through a regional logistics system

Increasingly, the debate on freight transport and logistics involves the challenge of sustainable development. Key objectives of sustainable or “green” freight logistics systems are the mitigation of negative environmental and human health effects of distribution operations and the realization of a major modal shift in transport preferences, while at the same time achieving internal generalized cost efficiency and quality of services. Pursuing these goals requires the introduction of a range of measures. These measures call for private and public actors to take up various initiatives and adopt policies. Usually, it is more effective to combine different actions into an integrated package of measures than to introduce single instruments in isolation.This article explores the nexus between sustainability and port hinterland container logistics. In particular, the methodology and results of an empirical analysis based on applications of a network programming tool called the “interport model” are presented and discussed. The model enables an examination of all possible effects on inland container flows and their associated internal and external costs due to public and private initiatives in the field of port hinterland container logistics. The empirical analysis aims to evaluate the impact of a set of simultaneous policy options and operational measures on the competitiveness and sustainability of hinterland multimodal distribution of import and export containers handled at the seaports of the Campania region located in Southern Italy. The loading units can transit through the dry port facilities (the so called “interports”) located in the same region and/or through extra regional railway terminals, before reaching their ultimate inland destinations or the seaports. The integrated package of measures simulated by means of the model includes: (i) infrastructure policy, (ii) improvements of rail services, (iii) regulatory changes in terms of customs authorizations and procedures, (iv) removal of technical and legal barriers to fair and non-discriminatory competition in the market of rail traction between regional seaports and interports, (v) new business models integrating container logistics operations between seaports and interports, and (vi) social marginal cost charging of transport operations. Once this package of instruments is introduced, higher private and social cost efficiency of port hinterland container distribution through the investigated regional logistics system can be achieved. For instance, it has been estimated an annual saving of the order of about 12,660 tonnes of CO₂ equivalent emissions from transport corresponding to an external cost reduction of 0.27 million euros from the observed real life situation, whereas the estimated saving in terms of air pollution (CO, NO_x, PM, SO₂, VOC) from transport is approximately 220 tonnes per year corresponding to an external benefit of 1.31 million euros.The most immediate priority appears to be the customs and intermodal logistics integration of seaports and interports by means of full implementation of the “extended gateway” concept as a way to increase the rail share of modal split and improve the overall cost efficiency of the system. In addition, the simultaneous introduction of a social marginal cost charging policy can contribute to make the regional interports a viable solution to expand the hinterland reach of the regional seaport cluster.     

An integrated framework for assessing service efficiency and stability of rail transit systems

A well-designed service plan efficiently utilizes its infrastructure and ensures an acceptable level of service stability with consideration of potential incidents that disturb or disrupt the rail transit services. To perform service evaluation, an integrated process combining capacity, resource usage, and system reliability is required to quantify service efficiency and stability in a consistent way. This study adopts capacity-based indices, “capacity utilization” and “expected recovery time”, as the attributes for service efficiency and stability, and develops a comprehensive evaluation framework with three corresponding modules to incorporate capacity, service plan, and system reliability and maintainability simultaneously. The capacity analysis module computes the rail transit capacities under normal and degraded operations. The reliability module classifies and fits the proper reliability and maintainability distributions to the historical interruption data. The service efficiency and stability module analyzes the results of the previous two modules and evaluates the service efficiency and stability of rail transit service plans. Empirical results show that the established evaluation framework can not only evaluate the service efficiency and stability but also identify critical sections and time slots. This tool can help rail transit operators rapidly assess their operational changes and investment strategies related to efficiency and stability so as to provide efficient and stable services to their customers.     

Refocusing the Modelling of Freight Distribution: Development of an Economic-Based Framework to Evaluate Supply Chain Behaviour in Response to Congestion Charging

The distribution of freight is a major contributor to the levels of traffic congestion in cities. However it is much neglected in the research and planning activities of government, where the focus is disproportionately on passenger vehicle movements. Despite the recent recognition of the contribution of freight transportation to the performance of urban areas under the rubric of city logistics, we see a void in the study of how the stakeholders in the supply chain might cooperate through participation in distribution networks, to reduce the costs associated with traffic congestion. Given that transport costs are typically over 45 of all distribution costs, with congestion a major contributor in the urban setting, the importance of establishing ways in which supply chain partnerships might cooperate to reduce levels of freight vehicle movements has much merit. This paper sets out a framework to investigate how agents in a retail supply chain might interact more effectively to reduce the costs of urban freight distribution. We propose an interactive agency choice method as a way of formalising a framework for studying the preferences of participants in the supply chain to support specific policy initiatives. Such a framework is a powerful way of investigating the behavioural response of each agent to many policies, including congestion pricing, as a way of improving the efficient flow of traffic in cities.     

Taxicab deregulation: Economic consequences and regulatory choices

The regulation of taxicab services is receiving an increasing amount of attention by city governments. At issue are the questions of whether local regulations should limit the supply of taxicabs and whether the regulations should control taxi fares.Recently, deregulation has become a popular suggestion; however, little empirical or theoretical evidence has existed to indicate the effects of taxi deregulations. This paper discusses these effects within a framework of eight regulatory scenarios involving different price, entry, and industry concentration factors. The analysis provides support for a public brokerage function.The preparation of this paper was supported, in part, by a contract from the Urban Mass Transportation Administration, U.S. Department of Transportation, Washington, DC.     

Analysis of factors that may be essential in the decision to fly on fully autonomous passenger airliners

This research investigates factors that influence opinion in the decision to fly on fully autonomous passenger airliners primarily from the perspective of aviation and technology professionals. Bayesian statistical inference and a two‐level fractional factorial survey are used to sample passengers' views on fully autonomous airliners. Eight trust, safety, and cost factors are incorporated into a vignette set in the future. Factors include automation levels, safety records, liability guarantees, airline integrity, and service disruptions. Dependent variables exist in five post‐vignette questions and essentially ask “Would you” or “Would you not” be willing to fly on a fully autonomous airliner? Sixteen versions of the vignette, each with unique trust, safety, and cost levels, present varying (unknown) degrees of influence to the survey respondents. For every demographic, the research shows a 99% statistically significant difference between the “prior” and “posterior” sampled population proportions willing to fly. The most significant positive influence involves integrity characteristics of the airline, while the most negative influence relates to life insurance liability guarantees. Research from 2003 suggested that this mode of travel would be acceptable to only 10.5% of respondents. When the 2003 research is used as a Bayesian prior probability, the resulting posterior probability for the demographics sampled can be modeled as a beta distribution, indicating 95% probability that the sampled proportion of the population willing to fly is between 33.2% and 36.4%. After adjusting for age and profession demographics to match the US population, the 95% probability bounds on the proportion willing to fly are 31.35% and 34.15%. Copyright © 2015 John Wiley & Sons, Ltd.     

“Comparing guideway transit implementation plans,including the impact on road traffic”

A methodology for comparing phased implementation plans for a new fixed guideway transit system in an urban area is presented. Four assumptions are made: (1) the guideway system replaces existing or planned bus service, (2) superior service on the new system results in increased ridership when compared to buses; (3) presence of the guideway facility redirects outward urban growth resulting in additional ridership, and (4) conversely, the absence of any action on the new guideway facility reinforces a diffuse urban growth pattern that creates an irreversible loss of transit ridership. The economic comparision of alternative plans includes total as well as “relative” inflation of principal cost components. A key feature of the proposed methodology is including in the comparisons the costs of private automobile mileage that could have been replaced by transit. These costs are expressed as “fuel” and “all other” automobile costs; favorable transit system implementation schedules can then be identified as a function of parametrically assumed values for these two unit costs. A hypothetical example demonstrates the proposed method.