Optimizing road network daily maintenance operations with stochastic service and travel times

This paper studies optimization methods for a routing problem encountered in daily maintenance operations of a road network. Stochastic service and travel times on road segments are considered. The problem is formulated as a variation of the capacitated arc routing problem (CARP). A chance-constrained programming model is firstly developed and solved by a branch-and-cut algorithm. A stochastic programming model with recourse is also proposed to take into account the recourse costs in case of route failure. The problem is solved by an adaptive large neighborhood search algorithm. The computational experiments demonstrate the effectiveness of the algorithm.     

A hybrid parallel genetic algorithm for yard crane scheduling

This paper aims at postulating a novel strategy in terms of yard crane scheduling. In this study, a dynamic scheduling model using objective programming for yard cranes is initially developed based on rolling-horizon approach. To resolve the NP-complete problem regarding the yard crane scheduling, a hybrid algorithm, which employs heuristic rules and parallel genetic algorithm (PGA), is then employed. Then a simulation model is developed for evaluating this approach. Finally, numerical experiments on a specific container terminal yard are used for system illustration. Computational results suggest that the proposed method is able to solve the problem efficiently.     

Integrating berth allocation and quay crane assignments

In this study, a dynamic allocation model using objective programming for berth allocation and quay crane assignments was preliminarily developed based on rolling-horizon approach. Afterwards, a hybrid parallel genetic algorithm (HPGA), which combined parallel genetic algorithm (PGA) and heuristic algorithm, was employed to resolve the proposed model. Furthermore, a simulation was conducted to evaluate the HPGA and to execute relevant gene repair techniques. Eventually, the numerical experiments on a specific container terminal were applied to illustrate the proposed models and algorithms. In so doing, the effectiveness of the proposed approach was verified.     

Variable neighborhood search heuristic for storage location assignment and storage/retrieval scheduling under shared storage in multi-shuttle automated storage/retrieval systems

This paper examines the joint optimization of storage location assignment and storage/retrieval scheduling in multi-shuttle automated storage/retrieval systems (AS/RSs) under shared storage, in which the reuse of empty location yielded by retrieval operation is allowed. From the view of analytical model, the advantage of operational mode under shared storage is verified. A variable neighborhood search (VNS) algorithm is developed to solve the large-sized problems. Various numerical experiments are conducted to evaluate the performance of the proposed algorithm and investigate the impact of different parameters on computational efficiency.     

Sailing speed optimization for container ships in a liner shipping network

This paper first calibrates the bunker consumption - sailing speed relation for container ships using historical operating data from a global liner shipping company. It proceeds to investigate the optimal sailing speed of container ships on each leg of each ship route in a liner shipping network while considering transshipment and container routing. This problem is formulated as a mixed-integer nonlinear programming model. In view of the convexity, non-negativity, and univariate properties of the bunker consumption function, an efficient outer-approximation method is proposed to obtain an ε-optimal solution with a predetermined optimality tolerance level ε. The proposed model and algorithm is applied to a real case study for a global liner shipping company.     

The heterogeneous green vehicle routing and scheduling problem with time-varying traffic congestion

The green vehicle routing and scheduling problem (GVRSP) aims to minimize green-house gas emissions in logistics systems through better planning of deliveries/pickups made by a fleet of vehicles. We define a new mixed integer liner programming (MIP) model which considers heterogeneous vehicles, time-varying traffic congestion, customer/vehicle time window constraints, the impact of vehicle loads on emissions, and vehicle capacity/range constraints in the GVRSP. The proposed model allows vehicles to stop on arcs, which is shown to reduce emissions up to additional 8% on simulated data. A hybrid algorithm of MIP and iterated neighborhood search is proposed to solve the problem.     

Social satisfaction,commuting and neighborhoods

Participation in social activities and the formation of social ties, networks, and capital are crucial in shaping not only the quality of life and health of an individual, but also in creating socially sustainable communities. This paper examines to what extent the urban environment shapes an individual’s level of satisfaction with his or her social contacts. A particular emphasis is placed on isolating the role of commuting times in impeding this outcome. The city of Vienna, Austria, is used as a case study. A statistical model considers elements of an individual’s neighborhood including population density and urban centrality, as well as personal characteristics and transportation-related factors. Results indicate that those with one-way commutes of 30 min or longer result in lower levels of social satisfaction. Residing in a neighborhood with high transit level of service and car ownership positively impact social satisfaction.     

Operationalization of path walkability for sustainable transportation

Most walking travel behavior research thus far has tested area-based neighborhood walkability, which is measured with meso-level urban form attributes. In need of micro-level walkability analyses that focus on individual travelers and their routes, we propose a route-oriented linear walkability concept named “path walkability.” It is defined and measured by 42 path walkability indicators that can collectively represent an individual traveler's micro-level walkability. A graphic measurement instrument for an objective and efficient on-field walkability measurement is developed. This study also sets the protocol for quantitatively integrating the walkability data measured at the segment level into path walkability indicators that are comparable at the route level. To test the applicability of the proposed path walkability, a pilot case study is conducted within a station area. A user survey is administered to collect transit users' access mode choices and walking routes to the station. The survey results help identify two groups of street segments: one used by regular walkers and the other selected by habitual auto users/occasional walkers. The routes chosen by the two groups are quantitatively and graphically compared for walkability. The analyses show a physically measurable and quantitatively comparable difference between the routes' walkability and suggest criteria for walking-conducive transit walkability for station users. Specific design recommendations for improving street-level micro-walkability for future transit-oriented developments (TODs) are added along with a future research agenda.     

Auditing street walkability and associated social inequalities for planning implications

Transport planning is gradually shifting targets towards modifying the pedestrian streetscapes that favor walking and enhance urban sustainability. We cannot be optimistic about walkability on condition that walkable streets are not evenly distributed within urban settings. Auditing the street walkability and associated social inequalities in developing countries should provide critical implications for transport planning. This paper identifies the most common indicators in existing indicator classification frameworks based on word frequency; and then establishes an indicator classification system (connectivity, accessibility, suitability, serviceability, and perceptibility) through expert panel evaluation for auditing street walkability in China. Using a case of Hangzhou metropolitan area, a set of 13 indicators are first selected by referring to the established indicator classification system and then aggregated into an integrated walkability index (IWI) through the catastrophe theory (CT) model after appropriate data treatment (standardization, normalization and correlation calculation). Camera signaling data are employed to validate the developed IWI. Results show that IWI is efficient to audit street walkability. IWI presents great heterogeneity at segment level. In general, higher walkability is observed in streets across the central and western areas. Walkability profiles of the segments are further produced by the clustering approach and the categorized groups can inform more targeted planning options. Spatial regression is finally utilized to quantify the associations between community socio-demographics and neighborhood IWI at two levels. We discover that lower neighborhood walkability would be observed in socioeconomically disadvantaged communities. These results suggest that significant social inequalities in street walkability should exist across the communities within Hangzhou metropolitan area. The developed IWI not only brings a standardized measurement of street walkability in the field of transport planning, but also paves the way for addressing the social inequalities in street design across various jurisdictions.     

Demand-responsive transit circulator service network design

Commuter rail systems are being introduced into many urban areas as an alternative mode to automobiles for commuting trips. It is anticipated that the shift from the auto mode to rail mode can greatly help alleviate traffic congestion in urban road networks. However, the right-of-way of many existing commuter rail systems is usually not ideally located. Since the locations of rail systems were typically chosen long ago to serve the needs of freight customers, the majority of current commuter rail passengers have to take a non-walkable connecting trip to reach their final destinations after departing the most conveniently located rail stations. To make rail a more viable commuting option and thus more competitive to the auto mode, a bus feeder or circulator system is proposed for transporting passengers from their departing rail stations to final work destinations in a seamless transfer manner. The key research question with operating such a bus circulator system is how to optimally determine a bus route and stopping sequence for each circulating tour by using the real-time demand information. In this paper, we name this joint routing and stopping optimization problem the circulator service network design problem, the objective of which is to minimize the total tour cost incurred to bus passengers and operators with respect to minimizing the walk time of each individual bus passenger. A bi-level nonlinear mixed integer programming model is constructed and a tabu search method with different local search strategies and neighborhood evaluation methods is then developed for tackling the circulator service network design problem.     

Optimal allocation of protective resources in urban rail transit networks against intentional attacks

This paper advances the field of network interdiction analysis by introducing an application to the urban rail transit network, deploying protective resources against intentional attacks. The resource allocation problem for urban rail transit systems is considered as a game between two players, the attacker interdicting certain rail stations to generate greatest disruption impact and the system defender fortifying the network to maximize the system’s robustness to external interdictions. This paper introduces a game-theoretic approach for enhancing urban transit networks’ robustness to intentional disruptions via optimally allocating protection resources. A tri-level defender–attacker–user game-theoretic model is developed to allocate protective resources among rail stations in the rail transit network. This paper is distinguished with previous studies in that more sophisticated interdiction behaviors by the attacker, such as coordinated attack on multiple locations and various attacking intensities, are specifically considered. Besides, a more complex multi-commodity network flow model is employed to model the commuter travel pattern in the degraded rail network after interdiction. An effective nested variable neighborhood search method is devised to obtain the solution to the game in an efficient manner. A case study based on the Singapore rail transit system and actual travel demand data is finally carried out to assess the protective resources’ effectiveness against intentional attacks.     

Development and application of a dynamic model for road port access and its impacts on port-city relationship indicators

Seaports are major intermodal structures in the global supply chain, where multiple stakeholders search for profitable and resilient maritime lines. Shipowners reduce the distance between the northern and southern hemispheres by connecting hub ports. Hosting a global hub port implies competitive advantages to the municipality. However, operational bottlenecks loosen the port-city relationship. One of the main conflicts in this relation is the land port access, a hard-to-be-mapped, random operation. The traffic flow rise noticed in developed countries' ports and, more recently, in emerging markets, causes congestion and air pollutant emissions in terminal surroundings. Current models for road port access are static, single-window non-synchronized truck appointment systems. As a contribution, this case study develops a dynamic model of road port access. Also, it verifies the effectiveness of its application in the port-city relationship indicators in an emerging market global hub port, the Port of Santos, faced with ports of developed countries, prospecting optimal conditions to its implementation in an environment with significant institutional obstacles.     

Analysis of global marine oil trade based on automatic identification system (AIS) data

A fine-grained analysis framework of global marine oil trade based on AIS data is developed to address the existing problems of using statistical data to analyze oil trade without sufficient temporal and spatial resolution. The framework includes three modules: traffic route analysis, trade volume analysis, and trade network analysis. A ship cargo payload calculation (SCPC) model is proposed to take the draught, shape, and size of the vessel and seawater density into consideration. It calculates the oil trade volume of each oil tanker voyage as a unit. More than 3.4 billion global automatic identification system (AIS) records in 2017 are utilized to verify the proposed framework and achieve the following findings. The Middle East-Strait of Malacca-East Asia oil transport route is the busiest and largest trade volume route in the global marine oil trade. The oil trade volume of the world's top 20 oil-importing and oil-exporting countries calculated based on AIS data is strongly correlated to the Joint Organizations Data Initiative (JODI) statistics with the determination coefficient (R²) of 0.8798. More than 90% of the world's top 20 oil-importing and oil-exporting countries have more than five oil trading partners. The experimental results show that the proposed analysis framework has utilized the most minimal research object, every oil tanker's trajectory, to realize the fine-grained research of marine oil trade based on oil tanker flows analysis. The derived oil flows with directions and trade volumes provide the basis for constructing a directed weighted oil trade network.     

Model and algorithm for an unpaired pickup and delivery vehicle routing problem with split loads

This paper addresses the routing problem with unpaired pickup and delivery with split loads. An interesting factor of our problem is that the quantity and place for pickup and delivery are decision variables in the network. We develop an easy-to-implement heuristic in order to gain an efficient and feasible solution quickly. Then, a local search algorithm based on the variable neighborhood search (VNS) method is developed to improve the performance of the heuristic. Computational results show that the proposed VNS method is able to obtain an optimal or near optimal solution in reasonable time for the formulated problem.     

Estimating pedestrian and cyclist activity at the neighborhood scale

In most parts of the U.S., data on bicycle and pedestrian activity at the neighborhood scale are sparse or non-existent, despite the importance of such data for local planning. Here, a simple small-area estimation method is used to pair travel survey with land use and census data to estimate cyclist and pedestrian activity for census tracts in the state of California. This method is an improvement on fixed per-capita estimates of activity based only on regional or statewide averages. These activity estimates are then used to calculate the intensity of road use by cyclists and pedestrians, and crash rates for these road users. For California, the intensity of pedestrian and cyclist road use in urban census tracts is double that found in suburban tracts, while use in suburban tracts is an order of magnitude greater than that found in rural tracts. Per-capita estimates would suggest substantially smaller differences between neighborhood types. On the safety side, although non-severe crashes involving cyclists and pedestrians are much more likely in more urban areas, severe crash rates for the non-motorized modes exhibit no clear spatial pattern. The method used is simple and easily replicable, potentially filling a critical need for bicycle and pedestrian planners.     

A humanitarian logistics model for disaster relief operation considering network failure and standard relief time: A case study on San Francisco district

We propose a multi-depot location-routing model considering network failure, multiple uses of vehicles, and standard relief time. The model determines the locations of local depots and routing for last mile distribution after an earthquake. The model is extended to a two-stage stochastic program with random travel time to ascertain the locations of distribution centers. Small instances have been solved to optimality in GAMS. A variable neighborhood search algorithm is devised to solve the deterministic model. Computational results of our case study show that the unsatisfied demands can be significantly reduced at the cost of higher number of local depots and vehicles.     

Operationalizing the concept of neighborhood: Application to residential location choice analysis

In this paper, we explore different conceptualizations to represent neighborhoods in residential location choice models, and describe three alternative ways for constructing operational units to represent neighborhoods. In particular, we examine the possibility of using the census units to represent the hierarchical ‘fixed neighborhood’ definition, and the circular units and network bands to represent the hierarchical ‘sliding neighborhood’ definition. Overall, the network band definition is conceptually appealing. It also is marginally superior to the other two operational representations from a model fit standpoint.     

The planning and real-time adjustment of courier routing and scheduling under stochastic travel times and demands

This study develops a planning and a real-time adjustment model to plan courier routes and schedules in an urban area and to adjust the planned routes in actual operations. The stochastic travel time aspect of the problem has been addressed at both the planning stage and the operation stage. A heuristic is developed to efficiently solve the stochastic real-time adjustment model and a simulation-based evaluation method is also developed to compare the performance of the proposed models. The test results, related to an international express company’s operations, show the good performance of the proposed models.     

Effects of neighborhood types & socio-demographics on activity space

This paper examines the relationships between socio-demographic characteristics, travel time, the built environment and resulting average activity spaces for all activities and non-work activities separately using data from the 2012 Northeast Ohio Regional Travel Survey. Multiple regression models are developed to analyze these relationships at individual level. First K-means cluster analysis is conducted to create seven neighborhood types based on five built environment variables. These new neighborhood types are used as discrete explanatory variables to explain average activity spaces, while controlling for travel time, individual and household features, access to transit facilities and the job-population balance. The modeling results indicate that residential location characteristics have significant influences on activity spaces. People living in places away from suburban and rural areas and with a high mix of population and employment tend to have smaller activity spaces. Moreover, this study finds out that while the effects of some explanatory variables (such as age and gender) vary for all activities and non-work activities, socially disadvantaged people (such as the elderly and low income households) generally experience smaller activity spaces.     

Determining the Critical Success Factors of the Wine Tourism Region of Napa from a Supply Perspective

Napa is a renowned region for wine tourism and demonstrates how wine can be an instrument to develop tourism. The purpose of this research is to identify the critical success factors that have shaped the area's rise and growth, and its unique competitiveness in both the domestic and global marketplaces for wine tourism destinations. The findings from the research provide the foundation for a proposed conceptual model of success factors in wine tourism research and as insight to practitioners/suppliers. Findings reveal an aligned marketing effort and strategic partnerships among suppliers of Napa wine tourism. Copyright © 2013 John Wiley & Sons, Ltd.