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.     

Vector network equilibrium problems with capacity constraints of arcs

In this paper, we study a (weak) vector equilibrium principle with capacity constraints of arcs and common arcs in some different paths. We obtain some necessary and sufficient conditions for a (weak) vector minimum cost flow. By virtue of a (weak) Δ-equilibrium principle, we also derive some necessary and sufficient conditions for a weak vector equilibrium flow.     

Refueling-station location problem under uncertainty

In this paper, we introduce a two-stage stochastic refueling station location model, where the first stage locates permanent stations and the second locates portable stations. The portable alternative fuel stations are an innovative feature in transportation network. The models are applied to an intercity network for Arizona. Computational results show that the permanent stations locate in and around heavily populated nodes. In addition, the results obtained for the portable stations can be utilized to set up permanent stations when the investor intends to increase the number of such stations. The computational results of the exact and greedy approach are reported.     

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.     

Tourism travel under climate change mitigation constraints

The paper first describes an inventory for 2005 giving the tourism related CO₂ emission caused by global tourism, and presents a 30-year projection and a 45-year simulation. The study found that tourists cause 4.4% of global CO₂ emissions. Also these emissions are projected to grow at an average rate of 3.2% per year up to 2035. This increase is problematic as globally a reduction of emissions by 3–6% is required to avoid ‘dangerous’ climate change. Using contemporary scenario techniques it appeared difficult to find a future tourist travel system consistent with CO₂ emission reductions of up to 70% by 2050 with respect to 2005. Based on the model underlying the 30-year projection, 70 scenarios are presented in a ‘landscape’ graph exploring the effect of opportunities to reduce the emissions, but this attempt did not reach the large reductions envisaged. We therefore explored automated scenario generation as a way to define backcasting scenarios that both reach the emission reduction target and retain the highest possible economic value for the sector. The main contributions made by this study are (1) in comparing the value of different ways to approach a (desired) future and (2) giving insight into the kind of structural changes required within tourism and tourism transport in case very strong emission reductions are required. Finally the model showed signs of ‘complex’ behaviour.     

Airline delay management problem with airport capacity constraints and priority decisions

This paper deals with the Airline Delay Management Problem (ADMP), which can be described as the task of dealing with daily airline operational delays and deciding whether to delay subsequent flights at a hub airport or to have them departing on time. An innovative integer linear programming approach is presented to the capacitated case of the ADMP and airport limitations in terms of bay availability, taxiway capacity and runway separation are incorporated to represent capacity constraints. Fuel cost, passenger compensation, and passenger inconvenience costs are included in the objective function. The decision variables include the re-timing of flight departures and arrivals, the use of the airport capacity over time and the rebooking of passengers in case of missed connections. To guarantee the linearity of the optimization model and fast computational times, a receding horizon modeling framework is adopted. The approach is applied to a case study using real operational and passenger data from an international hub-and-spoke carrier. The case study shows the capability of the linear model to deal with a complete day of operations within a few minutes. The results suggest that the proposed approach can lead to cost reductions of almost 30% during recovery, when compared with the solution from the airline. In addition, a sensitivity analysis is provided to investigate the impact of not including passenger inconvenience costs and of reducing runway capacity.     

The competitive facility location problem under disruption risks

Two players sequentially locate a fixed number of facilities, competing to capture market share. Facilities face disruption risks, and each customer patronizes the nearest operational facility, regardless of who operates it. The problem therefore combines competitive location and location with disruptions. This combination has been absent from the literature. We model the problem as a Stackelberg game in which the leader locates facilities first, followed by the follower, and formulate the leader’s decision problem as a bilevel optimization problem. A variable neighborhood decomposition search heuristic which includes variable fixing and cut generation is developed. Computational results suggest that high quality solutions can be found quickly. Interesting managerial insights are drawn.     

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.     

The impact of airport capacity constraints on future growth in the US air transportation system

This paper simulates airline strategic decision making and its impact on passenger demand, flight delays and aircraft emissions. Passenger flows, aircraft operations, flight delays and aircraft emissions are simulated for 22 airports in the US, under three airport capacity scenarios. The simulation results indicate that most system-wide implications for operations and environmental impact seem to be manageable, but local impacts at congested hub airports may be significant. The response of the air transportation system to avoid airports with high delays could significantly impact passenger demand and air traffic for these and directly dependent airports. The simulations also suggest that frequency competition effects could maintain flight frequencies at high levels, preventing a significant shift toward larger aircraft, which would otherwise reduce the impact of the capacity constraints.     

A metaheuristic approach to the reliable location routing problem under disruptions

This paper examines a reliable capacitated location–routing problem in which depots are randomly disrupted. Customers whose depots fail must be reinserted into the routes of surviving depots. We present a scenario-based mixed-integer programming model to optimize depot location, outbound delivery routing, and backup plans. We design a metaheuristic algorithm that is based on a maximum-likelihood sampling method, route-reallocation improvement, two-stage neighborhood search and simulated annealing. Numerical tests show that the heuristic is able to generate results that would keep operating costs and failure costs well balanced. Managerial insights on scenario identification, facility deployment and model simplification are drawn.     

A supporting station model for reliable infrastructure location design under interdependent disruptions

This paper proposes a new modeling method that equivalently transforms interdependent and correlated facility failures in an infrastructure system into only i.i.d. disruptions in a supporting structure. The properties of this structure are examined and a mathematical model is created to solve reliable facility location design problems under correlated facility failure risks. This model is formulated into a compact integer linear program and can be efficiently solved by state-of-the-art solvers. A set of experiments and case studies are conducted to demonstrate the applicability of the proposed model and to draw managerial insights into the optimal system design.     

Hub premiums in European civil aviation

We investigate the practice of carriers that charge higher fares for flights leaving from their hub. We analyze this phenomenon by relating fares to distance, using the main leg of intercontinental flights for scaling purposes. Our results indicate that the practice of a mark up on flights originating from or going to hubs is not typical for the US situation. At least some European carriers charge significant premiums for direct flights from their hubs. We find that at least part of these premiums can be attributed to market power. Policy measures should be aimed at reduction of market power and consumer protection. Furthermore, the existence of hub premiums should be taken into account in regional hub policies.     

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.     

Existence and efficiency of oligopoly equilibrium under toll and capacity competition

This paper studies the existence and efficiency of oligopoly equilibrium under simultaneous toll and capacity competition in a parallel-link network subject to congestion. We establish sufficient conditions for the existence of a pure-strategy oligopoly equilibrium and then derive upper bounds on the efficiency loss of the oligopoly equilibrium over the social optimum under different inverse demand function assumptions, respectively. Furthermore, we show that these bounds are demand-function free and only dependent upon the number of competitive roads.     

西安北站综合交通枢纽规划方案

随着西成、大西客运专线,西银铁路,关中城际铁路等引入西安枢纽,西安北站在规划区内将形成集高速铁路客运、城市轨道交通、中长途公路客运、城市公交、出租汽车、社会车辆于一体的大型综合交通枢纽。在西安北站按一站三场设计方案的基础上,重点对各场间客车疏解线、站区规划、区域交通和站房及交通流线设计等进行了规划方案研究。     

综合运输枢纽内“零”换乘问题研究

近年来,随着国民经济的飞速发展,人们交流、出行次数增多,物资流动速度加快,促使交通运输业发生了根本性变化。同时,全球经济一体化和中国经济对外开放进程的加快,对我国交通运输一体化发展也提出了越来越高的要求,人们不再只注重单一的可达性,而是更加注重各种运输方式的舒适性、方便性、快捷性及各种运输方式之间换乘衔接的有效性。     

Reliable emergency service facility location under facility disruption,en-route congestion and in-facility queuing

The planning of emergency service facility location, especially for those expecting high demand and severe conditions, requires consideration of victims’ en-route travel, in-facility service quality, and reliability of these service facilities themselves. This paper first presents a scenario-based stochastic mixed-integer non-linear program (MINLP) model that integrates facility disruption risks, en-route traffic congestion and in-facility queuing delay into an integrated facility location problem. We derive lower and upper bounds to this highly complex problem by approximating the expected total system costs across the normal and all probabilistic facility disruption scenarios. This allows us to develop a more tractable approximate MINLP formulation and a Lagrangian Relaxation (LR) based solution approach. The relaxed sub-problem for location and service allocation decisions is further reformulated into a second-order conic program. Numerical experiments show that the approximate model and LR solution approach are capable of overcoming the computational difficulties associated with the problem. Interesting findings and managerial insights are obtained from a series of sensitivity analyses, e.g., regarding the importance of considering in-facility queuing in location design, and the significance of resource pooling on the optimal facility deployment.     

Expanding airport capacity of cities under uncertainty: Strategies to mitigate congestion

Airport capacity constraints are increasingly challenging the growth of air traffic. At the same time, decision-making about airport capacity investments is extremely complex, involving trade-offs. This paper’s objective is to optimise a privately owned airport system’s capacity investment decision in a city under demand uncertainty. Next to the investment size, our real options model incorporates the timing of the investment, as well as the cost of congestion. The results reveal that the larger a city’s initial airport capacity, the smaller its investment will relatively be and the lower the occupancy rate threshold at which investment will take place. We also show that, in case of a higher demand growth combined with more demand uncertainty, the city will benefit from a significantly larger investment, but made later at a higher occupancy rate. In this case, cities with a small initial capacity will sometimes even more than double current capacity. Higher airport charges and an increase in non-aeronautical revenues both lead to a later investment in more capacity, due to the increased project attractiveness. An increase in congestion costs results in a larger investment made earlier, in order to eliminate delays. Airport operational cost and capacity holding cost increases both lead to smaller investments.     

龙岩铁路枢纽运输方案研究

结合龙岩铁路枢纽设备及运输状况,分析龙厦铁路开通后枢纽内运输组织存在的问题,根据客、货运量预测,提出龙岩铁路枢纽运输组织方案,具体包括旅客列车开行方案、货物列车开行方案和枢纽内调小机车的运用方案.     

安康铁路枢纽改造方案的几点思考

在分析安康铁路枢纽现状及在建和拟建工程的基础上,针对安康铁路枢纽存在的问题,提出新设大岭铺—安康东联络线,解决枢纽东、北端运能紧张问题;新设西端货车外绕线和东端客车外绕线,实现枢纽内客货分线运行等建议。同时,根据安康铁路枢纽客、货运量预测,剖析客、货运站点合理分工布局及改造方案,以促进地方经济又好又快地发展。