1,721,012 research outputs found

    A New Hierarchical Architecture for Air Traffic Managment: Optimization of Airway's Capacity in a Free Flight Scenario

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    We describe a new two-level hierarchical architecture for air traffic management problems with corresponding mathematical models. The first level represents the air route network, and its solutions provide the air traffic flows on each arc of the network. This level interacts with the second one, which represents the single airway and its own air traffic flows. This latter model allows us to assign the optimal air traffic route to each aircraft and to optimise the airway's capacity. Furthermore, for the airway optimisation model we have also carried out a computational analysis, providing both exact and heuristic solutions, for problem instances based on real data. These are obtained with the Cplex solver exploiting the mixed integer mathematical formulation and with a proposed heuristic algorithm for problems of larger size, respectively. The heuristic solutions obtained are within a maximum gap of 13% from the LP relaxation

    A Dynamic Programmiig Approach for the Airport Capacity Allocation Problem

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    In most of the optimization models developed to manage airports operations, arrivals and departures capacities are treated as independent variables: that is the number of flights allowed to take off does not affect the number of landings in any unit of time, and vice versa. This assumption is seldom verified in most of the congested airports, where many interactions between arrivals and departures take place. In this paper, we face the problem of finding the optimal trade‐off between the number of arrivals and departures in order to reduce a delay function of all the flights, using a more realistic representation of the airport capacity, i.e. the capacity envelope. Under the assumption of piecewise linear convex capacity envelopes and of the exact interpolation of all the Pareto‐optimal operational points, we show that the problem can be formulated as a linear programming model. For general airport capacity envelopes, we propose a dynamic programming formulation with a corresponding backward solution algorithm, which is robust, easy to implement and has a linear computational complexity. The algorithm performances are evaluated on different realistic scenarios, and the optimal solutions are compared with those computed by a greedy algorithm, which can be seen as an approximation of the current decision procedures. The percentage deviation of the cost of these two solutions ranges from 3.98 to 35.64%

    The Air Traffic Flow Management Problem with Time Windows

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    This paper defines a set of temporal intervals, called time windows, which are defined prior to flight departure and constitute milestones to be met during the flight execution. The size of the time windows is variable as it reflects all known constraints, such as punctuality at destination, runway capacities or congested en-route areas that the flight will cross. Once a time window is defined, all the air traffic actors are committed to guarantee that flight operations, e.g. enter an airspace sector, depart from or arrive at an airport, are executed within the time window. We propose a two-step approach based on a mixed integer programming formulation. The first step determines a set of time windows such that the overall cost of delay is minimized. Then in the second step we choose the set of optimal time windows which also maximizes the overall time window size. In such a way, we provide to all air traffic stakeholders the largest degree of flexibility to perform their operations under the constraint that the minimum achievable delay is kept constant. We also gain information on the critical flights of the system: if the optimal width of a time window is equal to its minimum available value, any disruption that may cause the flight not to meet it may produce undesired downstream effects. Our preliminary computational experience based on small-scale random instances confirms that the flexibility granted to flights increases with the capacity while the system delay simultaneously decreases. We also show that when there is no congestion a non negligible share of small size time windows may exist, thus indicating the existence of bottlenecks and critical flights

    Granting flexible operations in congested airspaces

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    Several causes of delay are deterring the air transportation system from being efficient. System capacity reductions are the major cause of delay. However, there are also some other causes, directly imputable to airlines, which may produce, in combination with the capacity reductions, undesired downstream effects. Therefore, with the purpose of containing delays and disruptions in flight schedules, it is important to grant flexibility to flight operations. This paper presents a mathematical formulation that allows to determine the degree of flexibility given to flights by identifying through a set of temporal intervals, called time windows, those flights that have a larger impact on the air traffic system performances. A time window is a period of time during which a certain phase of the flight (e.g., take off, landing and entry into a sector) has to be executed. The size of the time windows is variable as it reflects system’s capacity constraints. The set of time windows, which maximizes the total width of the time windows, provides airline operators and air traffic control authorities with the largest degree of flexibility to perform their operations. Several formulations of the models are presented, which vary in the way of formulating the use of system capacity. However, by means of a computational analysis, we show that the solution of the time window model is insensitive to the formulation used for the capacity constraints
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