The reliable hub-and-spoke design problem: Models and algorithms

Hub-and-spoke structure is widely adopted in industry, especially in transportation and telecommunications applications. Although hub-and-spoke paradigm demonstrates significant advantages in improving network connectivity with less number of routes and saving operating cost, the failure of hubs and reactive disruption management could lead to substantial recovery cost to the operators. Thus, we propose a set of reliable hub-and-spoke network design models, where the selection of backup hubs and alternative routes are taken into consideration to proactively handle hub disruptions. To solve these nonlinear mixed integer formulations for reliable network design problems, Lagrangian relaxation and Branch-and-Bound methods are developed to efficiently obtain optimal solutions. Numerical experiments are conducted with respect to real data to demonstrate algorithm performance and to show that the resulting hub-and-spoke networks are more resilient to hub unavailability.     

A continuous approximation model for time definite many-to-many transportation

Time definite freight transportation carriers provide very reliable scheduled services between origin and destination terminals. They seek to reduce transportation costs through consolidation of shipments at hubs, but are restricted by the high levels of service to provide less circuitous routings. This paper develops a continuous approximation model for time definite transportation from many origins to many destinations. We consider a transportation carrier serving a fixed geographic region in which demand is modeled as a continuous distribution and time definite service levels are imposed by limiting the maximum travel distance via the hub network. Analytical expressions are developed for the optimal number of hubs, hub locations, and transportation costs. Computational results for an analogous discrete demand model are presented to illustrate the behavior observed with the continuous approximation models.     

The environmental cost implication of hub–hub versus hub by-pass flight networks

Increasing congestion at major hubs and the advantage to passengers of non-stop flights and faster journey times has intensified the debate on patterns of air service. At the same time the economics of highly focused networks has been challenged by the availability of very economic smaller capacity long-haul aircraft. The purpose of this research is to value the environmental costs of these two patterns of service: hub-to-hub and hub by-pass. Five long-haul markets were evaluated both on a hub to hub and hub by-pass basis. These involved both transatlantic and Europe/Asia flights. It was found that the noise and emissions social cost impact of the hub by-pass networks was significantly lower than the hub to hub in all cases. Differences in environmental costs per passenger depend on the concentration of population around the airports and the degree to which the hub routing involves extra mileage.     

Dispatching control at transfer stations in multi‐hub transit networks

Among dispatching control approaches, the holding option has attracted the most attention in bus control. However, holding a vehicle at a transfer station may exacerbate the delays because more passengers might accumulate at downstream stations and may also affect other connecting routes at other transfer stations. Our problem is to minimize the total costs of dispatching ready vehicles at each transfer station along coordinated routes in a multi‐hub transit network. The total costs include the waiting cost for on‐board passengers, the missed connection costs for late arrival passengers at the subject transfer station and possible transfer costs at downstream transfer stations. We develop a heuristic algorithm to optimize the holding times based on real time information about late vehicles. The results show that ready vehicles should be held longer when the arrival variances of late vehicles are small or when many late connecting passengers are expected.     

Solutions to the optimal network design problem with shipments related to transportation cost

Two versions of an optimal network design problem with shipments proportional to transportation costs are formulated. Extensions of an algorithm developed in prior research for solving these problems are proposed and tested. The performance of the algorithms is found to improve substantially as the dependence of shipments on costs is increased. Moreover, the optimal solutions obtained are unexpectedly robust with respect to a wide range of transportation cost assumptions. These findings could have important computational and policy implications if applicable to larger networks.     

Hub location with flow economies of scale

A characteristic feature of hub and spoke networks is the bundling of flows on the interhub links. This agglomeration of flows leads to reduced travel costs across the interhub links. Current models of hub location do not adequately model the scale economies of flow that accrue due to the agglomeration of flows. This paper shows that current hub location models, by assuming flow-independent costs, not only miscalculate total network cost, but may also erroneously select optimal hub locations and allocations. The model presented in this paper more explicitly models the scale economies that are generated on the interhub links and in doing so provides a more reliable model representation of the reality of hub and spoke networks.     

External costs of the Belgian interurban freight traffic: a network analysis of their internalisation

The strong expansion of freight road transports throughout Europe is an important source of congestion and pollution, as well as a cause of many accidents. To solve this problem will require the conjunction of many different remedies. One element of solution would be the promotion and substitution of transportation modes with less negative effects. This paper is focused on this solution. It presents some results obtained from a detailed GIS modelling of the Belgian multimodal freight transport network inserted within the overall trans-European network. It outlines the results of a simulation of the flows over the Belgian network in 1995 which allows to estimate some of the costs of several external effects of freight transports: the costs of pollution, congestion, accidents, noise and road damages. This paper provides also the simulated impacts on modal choice of a marginal external cost internalisation, and an estimation of the corresponding external cost savings.     

Fuel burn and environmental implications of airline hub networks

Hubs act as switching points for interactions and so are places through which flows are concentrated. This research uses the interactions between a system of cities as an experimental context for understanding selected environmental costs and benefits of concentrated flow. Whether hub based networks create additional environmental costs has been debated in the literature. In this paper, fuel burn is used as an indicator of environmental cost. The essential ideas are: (1) to examine fuel costs associated with larger aircraft; (2) to determine implications of higher loads on dense routes; and (3) to model the resulting implications for hub and gateway location. Variants of these questions apply to passenger and freight flows, and the paper will initially concentrate on passenger models.The paper shows that by modeling fuel burn and introducing a fixed charge (like a set up cost), a multiple allocation hub and spoke model can be adjusted to direct more or less flow onto the inter-facility connector. In other words, usage of multiple connections and direct links can be controlled and modeled as a function of the fixed charge. The resulting networks are characterized by quite different levels of passenger miles, aggregate fuel burn and fixed charges. The preferred network in terms of minimal fuel burn is found by subtracting the fixed set up charge, thereby focusing attention on the modeled fuel burn. The lowest cost set up is a network with a high degree of connectivity, and a pure single assignment hub network has the highest fuel cost (as a result of larger passenger miles needed by connecting paths). The data also allow a tabulation of total passenger miles, which, not surprisingly, track very closely with the fuel burn. In an interesting application of the ideas, it is shown that a fuel efficient network may require a large number of smaller regional jets, and in the interests of avoiding noise and congestion from so many extra airport operations, the carriers may choose to substitute a smaller number of larger planes, thereby slightly increasing fuel needs. This paper also provides a key ingredient for models of an international network where it is impossible to serve many long distance market pairs without consolidation.     

Finding optimal solutions for vehicle routing problem with pickup and delivery services with time windows: A dynamic programming approach based on state–space–time network representations

Optimization of on-demand transportation systems and ride-sharing services involves solving a class of complex vehicle routing problems with pickup and delivery with time windows (VRPPDTW). This paper first proposes a new time-discretized multi-commodity network flow model for the VRPPDTW based on the integration of vehicles’ carrying states within space–time transportation networks, so as to allow a joint optimization of passenger-to-vehicle assignment and turn-by-turn routing in congested transportation networks. Our three-dimensional state–space–time network construct is able to comprehensively enumerate possible transportation states at any given time along vehicle space–time paths, and further allows a forward dynamic programming solution algorithm to solve the single vehicle VRPPDTW problem. By utilizing a Lagrangian relaxation approach, the primal multi-vehicle routing problem is decomposed to a sequence of single vehicle routing sub-problems, with Lagrangian multipliers for individual passengers’ requests being updated by sub-gradient-based algorithms. We further discuss a number of search space reduction strategies and test our algorithms, implemented through a specialized program in C++, on medium-scale and large-scale transportation networks, namely the Chicago sketch and Phoenix regional networks.     

Life cycle emissions and cost model for urban light duty vehicles

The growth of vehicle sales and use internationally requires the consumption of significant quantities of energy and materials, and contributes to the deterioration of air-quality and climate conditions. Advanced propulsion systems and electric drive vehicles have substantially different characteristics and impacts. They require life cycle assessments and detailed comparisons with gasoline powered vehicles which, in turn, should lead to critical updates of traditional models and assumptions. For a comprehensive comparison of advanced and traditional light duty vehicles, a model is developed that integrates external costs, including emissions and time losses, with societal and consumer life cycle costs. Life cycle emissions and time losses are converted into costs for seven urban light duty vehicles. The results, which are based on vehicle technology characteristics and transportation impacts on environment, facilitate vehicle comparisons and support policy making in transportation. Substantially, more sustainable urban transportation can be achieved in the short-term by promoting policies that increase vehicle occupancy; in the intermediate-term by increasing the share of hybrid vehicles in the car market and in the long-term by the widespread use of electric vehicles. A sensitivity-analysis of life cost results revealed that vehicle costs change significantly for different geographical areas depending on vehicle taxation, pricing of gasoline, electric power and pollution. Current practices in carbon and air quality pricing favor oil and coal based technologies. However, increasing the cost of electricity from coal and other fossil fuels would increase the variable cost for electric vehicles, and tend to favor the variable cost of hybrid vehicles.     

Joint optimization of freight facility location and pavement infrastructure rehabilitation under network traffic equilibrium

Establishment of industry facilities often induces heavy vehicle traffic that exacerbates congestion and pavement deterioration in the neighboring highway network. While planning facility locations and land use developments, it is important to take into account the routing of freight vehicles, the impact on public traffic, as well as the planning of pavement rehabilitation. This paper presents an integrated facility location model that simultaneously considers traffic routing under congestion and pavement rehabilitation under deterioration. The objective is to minimize the total cost due to facility investment, transportation cost including traffic delay, and pavement life-cycle costs. Building upon analytical results on optimal pavement rehabilitation, the problem is formulated into a bi-level mixed-integer non-linear program (MINLP), with facility location, freight shipment routing and pavement rehabilitation decisions in the upper level and traffic equilibrium in the lower level. This problem is then reformulated into an equivalent single-level MINLP based on Karush–Kuhn–Tucker (KKT) conditions and approximation by piece-wise linear functions. Numerical experiments on hypothetical and empirical network examples are conducted to show performance of the proposed algorithm and to draw managerial insights.     

Weather impact on containership routing in closed seas: A chance-constraint optimization approach

Weather conditions have a strong effect on the operation of vessels and unavoidably influence total time at sea and associated transportation costs. The velocity and direction of the wind in particular may considerably affect travel speed of vessels and therefore the reliability of scheduled maritime services. This paper considers weather effects in containership routing; a stochastic model is developed for determining optimal routes for a homogeneous fleet performing pick-ups and deliveries of containers between a hub and several spoke ports, while incorporating travel time uncertainties attributed to the weather. The problem is originally formulated as a chance-constrained variant of the vehicle routing problem with simultaneous pick-ups and deliveries and time constraints and solved using a genetic algorithm. The model is implemented to a network of island ports of the Aegean Sea. Results on the application of algorithm reveal that a small fleet is sufficient enough to serve network’s islands, under the influence of minor delays. A sensitivity analysis based on alternative scenarios in the problem’s parameters, leads to encouraging conclusions with respect to the efficiency and robustness of the algorithm.     

Network design: selection and design of links and facility location

In this paper we introduce new network design problems. A network of potential links is given. Each link can be either constructed or not at a given cost. Also, each constructed link can be constructed either as a one-way or two-way link. The objective is to minimize the total construction and transportation costs. Two different transportation costs are considered: (i) traffic is generated between any pair of nodes and the transportation cost is the total cost for the users and (ii) demand for service is generated at each node and a facility is to be located on a node to satisfy the demand. The transportation cost in this case is the total cost for a round trip from the facility to each node and back. We will consider two options in regard to the links between nodes. They can either be two-way only, or mixed, with both two-way and one-way (in either direction) allowed. When these options are combined with the two objective functions, four basic problems are created. These problems are solved by a descent algorithm, simulated annealing, tabu search, and a genetic algorithm. Extensive computational results are presented.     

成都等交通物流融合发展经验与广州现代物流中心建设

本文根据实地调研成果,介绍了成都、重庆和郑州在建立健全物流管理体制机制、强化物流枢纽及通道功能、创新物流运输组织模式、物流标准化信息化、物流市场主体及产业培育等方面的先进经验,从加强政府顶层设计、完善物流枢纽和节点体系、促进物流枢纽互联互通、研究物流运输组织服务的新模式、打造“交通+物流+产业”的产业集群、提升物流标准化发展水平、出台促进物流降本增效的政策措施等七个方面总结了强化物流创新要素集聚,促进广州现代物流中心建设的经验和启示。     

A multi‐objective approach to the parcel express service delivery problem

Parcel express service in many countries assumes door‐to‐door delivery of parcels and small packages in the fastest possible way. Delivery companies usually organize hub delivery networks, as flows between hubs are characterized by the economy of scale effect. At hubs, parcels are exchanged across vans, trucks, and planes. To organize parcel delivery in a specific region, the parcel delivery company must make appropriate decisions about the total number of parcel delivery hubs, their locations, and the allocation of demand for facilities' services to facilities. These issues are modeled in this paper as a multi‐objective problem. The model developed is based on compromise programming and genetic algorithms. We also demonstrate in the paper an interactive manner in which a defined problem can be solved. The proposed model could be implemented in large‐scale networks. The paper also shows a case study of parcel delivery service in Serbia. Copyright © 2013 John Wiley & Sons, Ltd.     

The European freight railway system as a hub-and-spoke network

This paper addresses a hub-and-spoke network problem for railroad freight, where a central planner is to find transport routes, frequency of service, length of trains to be used, and transportation volume. Hub-and-spoke networks, often found in air freight, have not been favoured by railways in the past. Such a structure could be profitable, however, if there exist concentrated freight flows on some service links. We formulate a linear integer programming model whose objective function includes not only the typical operational cost, but also cost due to the transit time spent by freight in the network. We then develop heuristic algorithms to solve large scale instances occurring in rail freight systems in France plus Italy; Germany; and a 10-country European network. By assuming that every node is equipped with consolidation capability, we let the final solution naturally reveal potential hub locations, the impact of several of which is studied by sensitivity analysis.     

Network-oriented household activity pattern problem for system optimization

The recently emerging trend of self-driving vehicles and information sharing technologies, made available by private technology vendors, starts creating a revolutionary paradigm shift in the coming years for traveler mobility applications. By considering a deterministic traveler decision making framework at the household level in congested transportation networks, this paper aims to address the challenges of how to optimally schedule individuals’ daily travel patterns under the complex activity constraints and interactions. We reformulate two special cases of household activity pattern problem (HAPP) through a high-dimensional network construct, and offer a systematic comparison with the classical mathematical programming models proposed by Recker (1995). Furthermore, we consider the tight road capacity constraint as another special case of HAPP to model complex interactions between multiple household activity scheduling decisions, and this attempt offers another household-based framework for linking activity-based model (ABM) and dynamic traffic assignment (DTA) tools. Through embedding temporal and spatial relations among household members, vehicles and mandatory/optional activities in an integrated space-time-state network, we develop two 0–1 integer linear programming models that can seamlessly incorporate constraints for a number of key decisions related to vehicle selection, activity performing and ridesharing patterns under congested networks. The well-structured network models can be directly solved by standard optimization solvers, and further converted to a set of time-dependent state-dependent least cost path-finding problems through Lagrangian relaxation, which permit the use of computationally efficient algorithms on large-scale high-fidelity transportation networks.     

Transportation serviceability analysis for metropolitan commuting corridors based on modal choice modeling

Major commuting corridors in metropolitan areas generally comprise multiple transportation modes for commuters, such as transit (subways or buses), private vehicles, or park-and-ride combinations. During the morning peak hour, the commuters would choose one of the available transportation modes to travel through the corridors from rural/suburban living areas to urban working areas. This paper introduces a concept of transportation serviceability to evaluate a transportation mode’s service status in a specific link, route, road, or network during a certain period. The serviceability can be measured by the possibility that travelers choose a specific type of transportation service at a certain travel cost. The commuters’ modal-choice possibilities are calculated using a stochastic equilibrium model based on general travel cost. The modeling results illustrate how transportation serviceability is influenced by background traffic flow in a corridor, value of comfort for railway mode, and parking fee distribution.     

Network equilibrium for congested multi‐mode networks with elastic demand

This paper proposes an elastic demand network equilibrium model for networks with transit and walking modes. In Hong Kong, the multi‐mode transit system services over 90% of the total journeys and the demand on it is continuously increasing. Transit and walking modes are related to each other as transit passengers have to walk to and from transit stops. In this paper, the multi‐mode elastic‐demand network equilibrium problem is formulated as a variational inequality problem where the combined mode and route choices are modeled in a hierarchical logit structures and the total travel demand for each origin‐destination pair is explicitly given by an elastic demand function. In addition, the capacity constraint for transit vehicles and the effects of bi‐directional flows on walkways are considered in the proposed model. All these congestion effects are taken into account for modeling the travel choices. A solution algorithm is developed to solve the multi‐mode elastic‐demand network equilibrium model. It is based on a Block Gauss‐Seidel decomposition approach coupled with the method of successive averages. A numerical example is used to illustrate the application of the proposed model and solution algorithm.     

Designing personal rapid transit (PRT) networks

This paper presents a heuristic method for designing a PRT network. Because the PRT system operating characteristics and performance measures differ widely from those of conventional transit technologies, an algorithm for the PRT network design problem (NDP) is derived by using concepts from some current NDP algorithms. We minimize the sum of passenger travel time cost, construction cost, vehicle cost and operational costs, subject to an available budget of guideway, a maximum number of vehicles and given link capacities. Starting with a well-connected initial network, the algorithm eliminates and adds links iteratively as it searches for a near-optimal solution. If this solution satisfies the budget constraint, it is considered to be acceptable. Otherwise, additional links are deleted until a feasible near-optimal solution is obtained. The link elimination phase of the algorithm only considers half of the links at a time which greatly decreases computing time. None of the links in an acceptable solution will be overloaded.