Routing design for less-than-truckload motor carriers using Ant Colony Optimization

One of the most important challenges that confronts less-than-truckload carriers serving many-to-many distribution networks consists of determining how to consolidate flows of small shipments. The objective is to determine a route for each origin–destination pair that minimizes the cost while still guaranteeing a certain level of service. This research studies different aspects of the problem and provides a metaheuristic algorithm (based on Ant Colony Optimization techniques) capable of solving real-life problems in a reasonable computational time. The viability of the approach has been tested with a real case in Spain and encouraging results have been obtained.     

二次指派问题的蚁群算法研究

蚁群算法是受自然界蚂蚁觅食过程中,基于信息素的最短路径搜索食物行为启发,提出的一种智能优化算法。在采用蚁群算法求解二次指派问题中,针对蚁群算法存在的过早收敛问题,使用距离及流量作为启发式信息并引入局部优化,对蚁群算法的结果加以改进,计算机仿真结果表明,蚁群算法对求解二次指派问题有较好的效果。     

Using machine learning algorithms to predict the risk of small Unmanned Aircraft System violations in the National Airspace System

The increasing number of small Unmanned Aircraft System (sUAS) encounters with manned aircraft or airports increases the risk of collision in the National Airspace System. The purpose of this research is to develop and test predictive models for sUAS violation incidents in NAS using machine learning. This research uses machine learning algorithms to predict the risk of sUAS violation incidents using the FAA's UAS sighting data with a sample size of 2088. Three sUAS violation types are identified: flying above 400 feet, flying with 5 miles from an airport, and flying in restricted airspace. Seven machine learning algorithms were used, including classification regression, decision tree, neural network, gradient boosting, random forest, Bayesian networks, and Memory-Based Reasoning. The results show that Gradient boosting produces the best predictive model. This model can predict the sUAS violation incidents with an accuracy of 95.7 percent. Location, distance to the airport, state, sUAs altitude, airport type, and aircraft type are the most influential predictors to the sUAS violation incidents.     

A Lagrangian heuristic for the real-time vehicle rescheduling problem

When a public transit vehicle breaks down on a scheduled trip, one or more vehicles need to be rescheduled to serve that trip and other service trips originally scheduled for the disabled vehicle. In this paper, the vehicle rescheduling problem (VRSP) is investiaged to consider operating costs, schedule disruption costs, and trip cancellation costs. The VRSP is proven to be NP-hard, and a Lagrangian relaxation based insertion heuristic is developed. Extensive computational experiments on randomly generated problems are reported. The results show that the Lagrangian heuristic performs very well for solving the VRSP.     

Gentrification and the evolution of commuting behavior within America's urban cores, 2000–2015

This study examines recent changes (2000 - ~2015) in the socio-economic/demographic make-up of U.S. urban cores (UCs), and potential associations with commuting behavior including mode and time. Based on a sample of 101 UCs and their encompassing urbanized areas (UAs), the data suggest that UCs have undergone substantial demographic change during the first fifteen years of the 21st century, with key attributes of gentrification on the rise. At the same time, commuting via transit has declined faster within UCs than within their encompassing UAs, while the proportion of workers working from home and cycling to work grew faster than any other mode. Using data from the U.S. Census Bureau's decennial census and American Community Survey (ACS), a series of longitudinal regression models indicated several significant associations between common indicators of gentrification, including proportion of white/non-minority residents, home owners, young adults (18–39), household income, and proportion of college graduates, and changes in non-automotive commute modes (i.e. walking, cycling, transit). This may have implications for transportation infrastructure and policy as urban neighborhoods in the U.S. continue to undergo socio-economic/demographic change.     

Do owner–operators pose a safety risk on the nation’s highways?

Despite persistent claims in the motor carrier industry of poorer safety performance of owner–operators, there is little empirical work directly comparing owner–operator safety performance to that of employee drivers. This study assesses the statistical significance of differences in the safety performance between owner–operators and employee drivers. This study also expands on previous driver focused safety models by examining how driver and carrier characteristics affect safety performance. Data for this study were derived from the Motor Carrier Management Information System (MCMIS), and the Commercial Driver’s License Information System (CDLIS) databases. Study results provide evidence that owner–operators are associated with more driver- and vehicle-out-of-service violations but experience lower crash rates than do employee drivers.     

Continuity and change in American urban freeway networks

The American Interstate Highway System was created in 1944, though construction did not commence until 1956. During the planning process for this network the blueprint for American urban freeway systems was set in 1955 by a federal document called the Yellow Book. This provided about 100 maps of cities with planned urban freeway locations for the Interstate Highway System. A set of three basic network patterns were applied to these cities based on their size and location. In the half century since 1955 urban freeways in the Interstate System have expanded from a planned 2000 miles to over 16,600 miles, along with another 11,500 miles of non-Interstate freeways. The number of large metropolitan areas has increased tremendously while the monocentric commuting patterns of have been transformed. This paper explores how these urban freeway systems were applied to the country's urban geography of the 1950s and how they have adapted to changing populations and other transformations in American metropolitan areas in the last half century.     

A model for development of optimized feeder routes and coordinated schedules—A genetic algorithms approach

Many attempts have been made to solve bus route network design problems by splitting it in two stages, one for routing and the other for scheduling. Some researchers have made attempts to solve network design problems using non-traditional optimization techniques also, but not much has been done on modelling coordinated operations involving transfers from one mode to another. In this research, feeder routes and frequencies leading to schedule coordination of feeder buses with main transit are developed simultaneously using genetic algorithms. The coordinated schedules of feeder buses are determined for the existing given schedules of main transit. Thus the developed feeder routes and schedules are complementary to each other. As a case study the Dun Laoghaire Dublin Area Rapid Transit (DART) (heavy rail suburban service) station of Dublin in Ireland is selected. Finally the outcome of the research is a generated feeder route network for feeder buses and coordinated schedules of feeder buses for the existing schedules of DART at the selected station. The results of the proposed model indicate improved load factors on developed routes and also the overall load factor is also improved considerably as compared to the authors’ earlier model.     

A hybrid multi-objective approach to capacitated facility location with flexible store allocation for green logistics modeling

We propose an efficient evolutionary multi-objective optimization approach to the capacitated facility location–allocation problem (CFLP) for solving large instances that considers flexibility at the allocation level, where financial costs and CO₂ emissions are considered simultaneously. Our approach utilizes suitably adapted Lagrangian Relaxation models for dealing with costs and CO₂ emissions at the allocation level, within a multi-objective evolutionary framework at the location level. Thus our method assesses the robustness of each location solution with respect to our two objectives for customer allocation. We extend our exploration of selected solutions by considering a range of trade-offs for customer allocation.     

Exploratory Space–time Analysis of Inbound Tourism Flows to China Cities

The integration of space and time generates much closer interactions between geography and other social sciences in general while providing new perspectives for the role of geography in tourism flow studies. This paper aims to apply exploratory space–time analysis to provide insights into inbound tourism flow patterns in China's cities over the period of 2000–2009 using city‐level Geographical Information System datasets. First, this paper ascertains that there exists geographic neighborhood effect at city level by testifying significantly positive spatial autocorrelation. The hot spots and temporal stability are identified. The hot spots are locally concentrated in metropolitan areas. Local Markov matrix has also shown significant transitions with negative or positive influence of geographic neighbors upon a city. Specifically, three‐dimensional surface is created to visualize tourism flows. The spatial inequalities have the pattern of ‘the east more dense than the west, the south more dense than the north’. There simultaneously exist spatial agglomeration and spatial dispersion. The intensity of spatial agglomeration has become stronger. At the same time, smaller peaks of tourism flow centers developed around the main cities and spread toward surrounding cities. These potential tourism flow centers have gradually emerged and grown larger. Furthermore, the space–time covariance matrix uncovers correlation, which shows strong regional integration over years. Eight hundred and ninety links are identified and visualized. Two hundred and sixty nine links forming 10 spatial clusters represent strong positive correlation. One hundred and thirty‐four links are negative correlation, which is about 15.06 per cent of all links. In conclusion, our comprehensive evidences offer deeper insights and have important policy implications. These enable the tourism‐oriented governmental agencies, as well as the tourism industry professionals, to better understand the changes of inbound tourism flows in China's cities and relevant tourism partners/competitors for cities. Copyright © 2013 John Wiley & Sons, Ltd.     

Accessibility impacts of China’s high-speed rail network

The large-scale implementation of High-Speed Rail (HSR) network in China not only offers a new option for travelers’ mode choice, but also may influence, or even generate, the redistribution of demographic and economic activities. As has been observed over the past several years in other countries, the impact of HSR spans a wide range. However, few quantitative studies have been conducted to measure this impact. As a new attempt, this study uses accessibility analysis for quantifying the impact of China’s HSR network. Weighted average travel times and travel costs, contour measures, and potential accessibility are employed as indicators of accessibility at the macro or national level. Forty-nine major cities in the HSR network are used in the accessibility analysis. Accessibility quantification and spatial distribution analysis for the study cities are performed on a Geographical Information System (GIS) platform. Accessibilities associated with varying availabilities of HSR, conventional rail, and airline are estimated and compared. The selected indicators and computational methods are found effective in evaluating the accessibility impacts of HSR from different conceptualization strategies and perspectives. They also offer complementary information on accessibility capacity of the study cities created by the HSR network.     

Integrated scheduling of a multi-product multi-factory manufacturing system with maritime transport limits

This paper studies a practical multi-factory job allocation and scheduling problem involving inland and maritime transport limits. A new heuristic called Due-date Based Cut-off rule (DBC) is developed to improve the computational efficiency of both exact and genetic algorithms (GA). Except the application of DBC, this proposed GA is guided by a novel fuzzy controller aimed at eliminating the drawbacks other GAs have when dealing with multi-factory models. The tests of the solution quality and computational efficiency for this GA are carried out. The numerical experiments demonstrate the value of the proposed approach in this practical global supply chain.     

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

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

Three effective metaheuristics to solve the multi-depot multi-trip heterogeneous dial-a-ride problem

The Heterogeneous Dial-a-Ride Problem (HDARP) is an important problem in reduced mobility transportation. Recently, several extensions have been proposed towards more realistic applications of the problem. In this paper, a new variant called the Multi-Depot Multi-Trip Heterogeneous Dial-a-Ride Problem (MD-MT-HDARP) is considered. A mathematical programming formulation and three metaheuristics are proposed: an improved Adaptive Large Neighborhood Search (ALNS), Hybrid Bees Algorithm with Simulated Annealing (BA-SA), and Hybrid Bees Algorithm with Deterministic Annealing (BA-DA). Extensive experiments show the effectiveness of the proposed algorithms for solving the underlying problem. In addition, they are competitive to the current state-of-the-art algorithm on the MD-HDARP.     

European major airlines' strategic reactions to the Third Package

Since the Third Package in 1993, European Union (EU) registered airlines have been able to purchase majority ownership of other EU carriers and set up airlines in other EU countries. This paper investigates how European majors have responded to the liberalised policy, especially European Commission Regulation 2407/92. It goes on to analyse the impact of these strategies for airlines and the EU–US relationship in terms of airline alliances. It concludes that British Airways and the SAirGroup have pursued a policy of acquiring airlines in EU countries, with the former finding it an expensive and questionable strategy, and the latter disastrous.     

The partially private UK system for air traffic control

This paper reviews the publicly stated motives for establishing the UK system for air traffic control as a public–private partnership in 2001, and the significance of this public–private partnership as an example for the reform of other systems. It examines the performance of the PPP up to the present time in terms of safety, delays due to air traffic control, efficiency and financial performance. It attempts to relate actual performance to what would have occurred under alternative arrangements. It concludes that there is no demonstrable change due to the public–private partnership other than the financial result. It argues that the financial expectations of advocates of the PPP have not been fulfilled.     

Identification of land-use characteristics using bicycle sharing data: A deep learning approach

Extensive research has shown that urban land-use characteristics, including resident, work, consumption, transit, etc., are significantly interrelated with travel behaviors and travel demands. Many research efforts have been made to evaluate the impact of land use planning or policies on travel behavior, however, few studies are able to quantitatively measure the land-use characteristics based on the data of travel behaviors or travel demand. In this paper, a new hybrid model that combines time series feature extraction and deep neural network is proposed to identify regional land use characteristics and quantify land use intensity using ridership data of bicycle sharing. This method consists of four main parts: (i) A set of land-use characteristic labels are evaluated based on planning and Geographic Information System (GIS) data. (ii) An ensemble clustering method is used to determine the segmentation points of ridership time series. (iii) The statistical characteristics of the segmented time series are extracted and used as input to the neural network. (iv) A deep neural network is established and trained based on the processed ridership features and land-use labels. In terms of data collection, ridership data of the bicycle-sharing parking spots and land-use planning data are obtained from bicycle-sharing system and planning department in San Francisco Bay Area, California U.S.A., respectively. The test results show that this approach has high accuracy for identifying land-use characteristics based on several standard evaluation measures and that the identification distribution can be well explained. The extension results further prove that the model can be applied to effectively analyze the main land-use characteristics of the region although the identification results may become unstable after 3–4 months.     

The assessment of the EU–US Open Skies Agreement: The counterfactual and other difficulties

The advent of the EU–US Open Skies Agreement has been widely anticipated. A number of consequences have been predicted, for example, impacts on fares, on passenger volumes, choice and on consumer welfare. Airline costs are also predicted to fall as a result of increased competitiveness and increased cooperation among airlines. In the short period since the implementation of the Agreement, it is relatively easy to assess the supply-side changes that have been made, but more difficult to make wider judgements. For example, can traffic growth be attributed to Open Skies and does airline and alliance market power result in less fare flexibility with consequently less influence on changes in passenger volumes? Have airline costs changed and what has been the source of the savings? This paper offers some insight into the data that will be required to make these and other wider judgements and discusses some methodological difficulties.     

Causal nexus between the transport and logistics sector and trade: The case of Australia

Although a number of studies have already been conducted on the economic impact of the development of the transport and logistics sector and international trade, these are regarded as two separated topics, and little has been done so far to study in depth the relationship between them. This paper seeks to shed light on this issue in the context of Australia. To this end, the vector autocorrelation (VAR) framework is employed to explore the causal relationship between Australia–China trade and the development of the Australian transport and logistics sector. This framework is then extended to allow for the effect of Australia's trade with the US, Japan, the rest of the world and other variables. Based on the analysis results, implications for the transport and logistics sector are discussed.     

Optimal distance tolls under congestion pricing and continuously distributed value of time

This paper addresses the optimal distance-based toll design problem for cordon-based congestion pricing schemes. The optimal distance tolls are determined by a positive and non-decreasing toll-charge function with respect to the travel distance. Each feasible toll-charge function is evaluated by a probit-based SUE (Stochastic User Equilibrium) problem with elastic demand, asymmetric link travel time functions, and continuously distributed VOT, solved by a convergent Cost Averaging (CA) method. The toll design problem is formulated as a mixed-integer mathematical programming with equilibrium constraints (MPEC) model, which is solved by a Hybrid GA (Genetic Algorithm)–CA method. Finally, the proposed models and algorithms are assessed by two numerical examples.