Hub location problems in transportation networks

In this paper we propose a 4-index formulation for the uncapacitated multiple allocation hub location problem tailored for urban transport and liner shipping network design. This formulation is very tight and most of the tractable instances for MIP solvers are optimally solvable at the root node. While the existing state-of-the-art MIP solvers fail to solve even small size instances of problem, our accelerated and efficient primal (Benders) decomposition solves larger ones. In addition, a very efficient greedy heuristic, proven to be capable of obtaining high quality solutions, is proposed. We also introduce fixed cost values for Australian Post (AP) dataset.     

Sustainable hub location under mixed uncertainty

This paper addresses a novel sustainable hub location problem (SHLP) in which two new environmental-based cost functions accounting for air and noise pollution of vehicles are incorporated. To cope with uncertain data incorporated in the model, a mixed possibilistic–stochastic programming approach is proposed to construct the crisp counterpart. A simulated annealing (SA) and an imperialist competitive algorithm (ICA) with a new solution representation are developed to solve real-sized instances whose performances are compared with a proposed lower bound. Finally, some computational experiments are provided to demonstrate the effectiveness of the proposed model and solution approaches.     

Fleet deployment, network design and hub location of liner shipping companies

A mixed integer linear programming formulation is proposed for the simultaneous design of network and fleet deployment of a deep-sea liner service provider. The underlying network design problem is based on a 4-index (5-index by considering capacity type) formulation of the hub location problem which are known for their tightness. The demand is elastic in the sense that the service provider can accept any fraction of the origin–destination demand. We then propose a primal decomposition method to solve instances of the problem to optimality. Numerical results confirm superiority of our approach in comparison with a general-purpose mixed integer programming solver.     

Hub network design problems with profits

This paper presents a class of hub network design problems with profit-oriented objectives, which extend several families of classical hub location problems. Potential applications arise in the design of air and ground transportation networks. These problems include decisions on the origin/destination nodes that will be served as well as the activation of different types of edges, and consider the simultaneous optimization of the collected profit, setup cost of the hub network and transportation cost. Alternative models and integer programming formulations are proposed and analyzed. Results from computational experiments show the complexity of such models and highlight their superiority for decision-making.     

2-Stage stochastic programming approach for hub location problem under uncertainty: A case study of air network of Iran

In this paper 2-stage stochastic programming has been developed for formulating stochastic uncapacitated multiple allocation hub location problem. This problem is studied under three cases. The first, stochastic demand, the second, stochastic transportation cost and the third, integrated stochastic, which is compounded of first and second cases. A case of air network in Iran is used to evaluate proposed formulations and computational results obtained by GAMS are presented. The results show that considering uncertainty into formulation could cause in different solutions.     

Shelter location and transportation planning under hurricane conditions

This paper develops a scenario-based bilevel programming model to optimize the selection of shelter locations with explicit consideration of a range of possible hurricane events and the evacuation needs under each of those events. A realistic case study for the state of North Carolina is presented. Through the case study, we demonstrate (i) the criticality of considering multiple hurricane scenarios in the location of shelters, and; (ii) the importance of considering the transportation demands of all evacuees when selecting locations for public shelters.     

Hub competition and travel times in the world-wide airport network

The aim of this work is to measure the competition between airport hubs based on an analysis of travel times in the world-wide airport network. By considering the minimum travel time required to connect each pair of airports, it is possible to create new measures of hub competition, separating the effects of hub position and temporal coordination. This analysis was carried out at the global level, considering all 232 airports with more than 3 million seats yearly offered in departure flights in 2008, and also in relevant geographic markets. The results show a high level of competition among the most important world airports, but the major airports of Europe have a geographical advantage in relation to world markets over the major American and Asian airports. We also show that airports located in different continents often compete for the same origin–destination markets. Geographical position appears to be the most important variable explaining hub performance. Secondary hubs show a higher degree of specialization towards specific markets.     

Variations in hub service in the US domestic air transportation network

This paper looks at the various types of hubs that have evolved in the air transportation network in the USA. Since deregulation of the industry at the end of the 1970s, the major air carriers have expanded their networks to become more competitive, and the number and types of hubs have grown accordingly. A connectivity analysis using a traditional matrix approach is used to derive indices which are the basis for the development of a connectivity classification scheme. In addition, the various service functions of hubs are explored.     

Towards collaborative, intermodal hub networks: A case study in the fast moving consumer goods market

Collaborative hub networks can provide an answer to the need to decrease logistics cost and maintain logistics service levels by shifting consolidated flows to modes that are better suited for handling large volumes (rail, barge, coastal shipping), so economies of scale can be obtained. This necessity has been increased by the tendency of globalization of industries, smaller shipments sizes, high frequencies, and the fragmentation of flows. Through collaboration the necessary synchronization between expensive but fast and flexible means of transport and inexpensive, but slow and inflexible means can be combined in an intermodal hub network. This paper shows the rationale behind these collaborative hub networks, based on the literature on the design of many-to-many hub networks. The resulting methodology is explained through presenting the results of the design and implementation of collaborative hub network for the distribution of fast moving consumer goods using a combination of trucking and inland barges. This concept, first proposed by Vermunt [Vermunt, A.J.M., 1999. Multilognet, the intelligent multimodal logistics network, an important node in the worldwide logistics net, Vermunt Logistiek Advies v.o.f., working paper (in Dutch)], won the European Intermodal Award of the European Intermodal Association in 2003, and after extensive research was launched in The Netherlands as a commercial pilot by logistics service provider Vos Logistics and barge operator Riverhopper in January 2004.     

Warehouse location problems for air freight forwarders: a challenge created by the airport relocation

The move of Hong Kong International Airport from the city centre to a suburban area in July 1998 provided sufficient capacity to meet the increasing demand of passenger and air-cargo flows in Hong Kong in the foreseeable future. However, the move has adverse side effects such as causing the readjustment of many existing systems and creating many imminent strategic problems. One of such problems is the warehouse location of freight forwarders: they have to decide whether they should locate their warehouses in the new airport, in current locations, or in new locations somewhere in the city. This paper delineates the results of a survey conducted in the summer of 1997 before the airport was relocated. The survey asked what decisions the freight forwarders had made and how they evaluated some potential warehouse locations. The paper also considers two mathematical models, which explain and predict, respectively, the location pattern of freight forwarder warehouses before and after the relocation of the airport.     

Fulfillment source allocation,inventory transshipment,and customer order transfer in e-tailing

We consider an inventory fulfillment-allocation and transshipment problem in an e-tailing environment. For a typical e-tailer, each customer demand is fulfilled from the closest fulfillment center if there are enough inventories. Otherwise, the e-tailer would transship stock from a nearby facility or transfer the customer order so it is fulfilled from another facility, depending on the economics of transportation. We develop a mixed-integer programming model to help e-tailers optimally fulfill customer orders while minimizing logistics costs. We propose a Benders decomposition-based approach to efficiently find optimal solutions. Our computational results demonstrate the importance of considering inventory transshipments in online deliveries.     

Factors influencing the hub connectivity of Beijing Capital Airport in its international markets

This paper investigates factors influencing the hub connectivity of Beijing Capital Airport (PEK) in its domestic to international markets between 2014 and 2018 based on a random-effect panel data model. The results show that variables representing the temporal and spatial characteristics of connecting flights have significant impacts on the hub connectivity of PEK. In specific, the changeable threshold of maximum connecting time based on different international destination regions has a negative impact. This paper identifies different timetable coordination modes at PEK and shows that the number of indirect connections under adjacent mode is significantly less than that of distant mode. Circuity and directionality are proven to have significant impacts. In addition, factors representing airport characteristics and heterogeneity of international destination regions also affecting the hub connectivity of PEK.     

Supply-and-demand models for exploring relationships between smaller airports and neighboring hub airports in the U.S.

Airport passenger leakage is the phenomenon of air passengers choosing to travel longer distances to access more extensive air services offered by airlines at an out-of-region hub (or, substitute) airport, instead of using their local airports. Airport leakage can cause further reduction in services offered by airlines at a local airport, thereby causing even further leakage, and so on, which can significantly impact an airport's role in the growth of the local economy. This paper explores the geographic and operational attributes of local-and-substitute airport pairs in the United States, explicitly accounting for the interactive feedback relationship between passenger volumes and air service characteristics that contribute to the onset, persistence, and exacerbation of airport passenger leakage. A two-stage least squares regression model of air passenger demand at small- and medium-sized airports is first presented, where local passengers may travel by vehicle to larger, out-of-region hub airports. The results confirm that airfare and passenger volume relationships exist between the local and substitute airport pairs included in the dataset, and that lower airfares at the substitute airport have a greater impact on airport choices made by larger travel groups. They also suggest the existence of positive feedback in that if an airport attracts increasingly smaller passenger numbers with fewer air services and fewer air services with fewer passengers, without external intervention airport leakage impacts may be irreversible and exacerbate over time. A conceptual market share equilibrium analysis is used to illustrate the mechanisms of a direct two-way feedback relationship between passenger volumes at a local airport and air service characteristics at both the local and substitute airports. With data, this quantitative framework can help guide airport planners in further assessing and verifying suspected passenger leakage issues at their airport. The results suggest that without intervention, airport leakage impacts may be difficult to reverse; further exacerbating the trend are technological advancements that make driving cheaper and easier (connected and autonomous vehicles). However, the results can also guide planners in choosing the types and degrees of infrastructure investments and airline incentives that may be used to expand or retain air services to attract passengers.     

Optimisation of the exploitation period of individual vehicles in freight transportation companies

The individual vehicle replacement problem typical for freight transportation companies is discussed in the paper. Two characteristic features of such problem are that transportation companies utilise vehicles with intensity decreasing with an age of vehicles and that managers of such companies first of all take into account economical criteria when planning vehicle replacements. The paper presents a single criterion, nonlinear, deterministic and discrete mathematical model of such a problem that minimises a total exploitation and ownership costs calculated per kilometre. The exact solution procedure is proposed here. The problem is solved as a real life case study. As a result, an average, economically optimal 5-year exploitation period of vehicles has been determined.     

Combinatorial clock-proxy exchange for carrier collaboration in less than truck load transportation

A carrier collaboration problem in less-than-truck load transportation is considered, where multiple carriers exchange their pickup and delivery requests in order to improve their operational efficiency. We extend the clock-proxy auction proposed by Ausubel et al. (2006) to a combinatorial clock-proxy exchange for the problem. This mechanism combines the price discovery of the clock exchange designed based on Lagrangian relaxation with the efficiency of the proxy exchange determined based on the information observed in the clock phase. Numerical experiments on randomly generated instances demonstrate the necessity of the proxy phase and the effectiveness of the clock-proxy exchange.     

Regional transportation planning in the US: An examination of changes in technical aspects of the planning process in response to changing goals

This paper presents a framework for examining the ways in which technical aspects of the regional transportation planning process are changing in response to a broadening of goals and strategies, driven in part by an increased emphasis on public involvement. As an illustration of this framework, the long-range plans of four Metropolitan Planning Organizations (MPOs) in the US are analyzed with respect to goals, performance measures, and use of forecasts. These examples suggest that changes in the technical aspects of the process are lagging changes in planning goals. As a result, plans may implicitly emphasize congestion relief even if they put forth a much broader range of goals. This paper provides a basis for further analysis of the current evolution of transportation planning in the US.     

Handling uncertainties in vehicle routing problems through data preprocessing

This paper presents a global preprocessing methodology for handling uncertainties in operations management. Beyond theoretical considerations on solution feasibility, the methodology provides practitioners with a Monte Carlo simulation-based framework for effective risk management. The main strength of this methodology is being easily applicable to almost any decision problem. Application field of the paper is a real-life workforce management problem for which we propose several mixed integer formulations as well as dedicated solution algorithms. Extensive numerical tests on real-life instances assess the benefit from preprocessing schemes when performed as recommended by our approach, and thus prove its practical relevance.     

A systems-based approach to address unintended consequences of demand-driven transportation planning in national parks and public lands

In most cases, transportation planning in national parks and public lands might most appropriately be termed “demand-driven.” In this approach, rigorous analyses of park visitation, traffic, and parking data are used as a basis for transportation planning to accommodate current and projected future visitor demand, within financial constraints. Performance measures used to assess the quality of transportation systems in national parks are generally related to “moving people” efficiently. This approach is based on well-established principles for transportation planning in urban and rural communities. However, a demand-driven approach to transportation planning may not be suitable in national parks and public lands because it may enable levels of visitation that cause visitor crowding, resource impacts, and other unintended consequences. This paper introduces a more sustainable, systems-based transportation planning approach developed in the Rocky Mountain National Park (ROMO) to help the park operate its shuttle bus system efficiently and conveniently, and according to thresholds for visitor crowding and resource impacts at sites serviced by the shuttle system. The transportation planning approach developed in this study for ROMO is more suitable and sustainable for national parks and public lands than a demand-driven approach, and is readily adaptable to other locations. Correspondingly, the approach is now being applied in several other national parks and public lands recreation areas.     

Post-2010 FIFA Soccer World Cup: oversupply and location of luxury hotel rooms in Cape Town

An excess of hotel rooms in cities preparing to host a mega-event such as the FIFA Soccer World Cup is not a new occurrence. Between 2007 and 2010 the number of five-star hotel rooms in Cape Town increased by 50% and four-star hotel rooms by 20%. A spatial database of three-, four- and five-star hotels was compiled for the hotel sector of Cape Town. This paper reveals the global–local nexus of luxury hotel development in Cape Town (South Africa) and three different contexts in which the oversupply of hotel rooms must be understood. First is South Africa as a developing country engaged in hosting a hallmark event and engrossed in concomitant inflated tourism-related expectations. Second is the vulnerability of Cape Town's hotel sector with its overdependence on long-haul holiday tourists from a narrow northern-hemisphere market experiencing the worst economic recession since the 1930s. Third is the favourable economic trends in South Africa from 1999 to 2007 that have trapped hotel developers in a ‘fallacy of composition’.     

Accommodating spatial correlation across choice alternatives in discrete choice models: an application to modeling residential location choice behavior

This paper presents a modeling methodology capable of accounting for spatial correlation across choice alternatives in discrete choice modeling applications. Many location choice (e.g., residential location, workplace location, destination location) modeling contexts involve choice sets where alternatives are spatially correlated with one another due to unobserved factors. In the presence of such spatial correlation, traditional discrete choice modeling methods that are often based on the assumption of independence among choice alternatives are not appropriate. In this paper, a Generalized Spatially Correlated Logit (GSCL) model that allows one to represent the degree of spatial correlation as a function of a multi-dimensional vector of attributes characterizing each pair of location choice alternatives is formulated and presented. The formulation of the GSCL model allows one to accommodate alternative correlation mechanisms rather than pre-imposing restrictive correlation assumptions on the location choice alternatives. The model is applied to the analysis of residential location choice behavior using a sample of households drawn from the 2000 San Francisco Bay Area Travel Survey (BATS) data set. Model estimation results obtained from the GSCL are compared against those obtained using the standard multinomial logit (MNL) model and the spatially correlated logit (SCL) model where only correlations across neighboring (or adjacent) alternatives are accommodated. Model findings suggest that there is significant spatial correlation across alternatives that do not share a common boundary, and that the GSCL offers the ability to more accurately capture spatial location choice behavior.