Scatter Search and Bionomic Algorithms for the aircraft landing problem

The problem of deciding how to land aircraft approaching an airport involves assigning each aircraft to an appropriate runway, computing a landing sequence for each runway and scheduling the landing time for each aircraft. Runway allocation, sequencing and scheduling for each aircraft must ensure the scheduled landing time lies within a predefined time window and meet separation time requirements with other aircraft. The objective is to achieve effective runway use.In this paper, the multiple runway case of the static Aircraft Landing Problem is considered. Two heuristic techniques are presented: Scatter Search and the Bionomic Algorithm, population heuristic approaches that have not been applied to this problem before.Computational results are presented for publicly available test problems involving up to 500 aircraft and five runways showing that feasible solutions of good quality can be produced relatively quickly.     

基于优先级的进离港航班排序优化问题研究

研究机场终端区进离港航班排序优化问题,对于提高跑道利用率以及降低航班延误损失具有重要意义。本文首先考虑航班运行方式(降落和起飞)、飞机类型以及航班的重要程度(航程是否连续)的不同所造成延误损失的不同,设计三维优先级表反映调度优先等级,并将其转化为延误成本系数。其次,为实现调度的公平性和减轻管制人员的工作负荷,设置允许延误的航班架次约束、邻边约束以及最大限制位置约束。再次,以最小化航班总延误成本为目标建立模型,提出相应的改进蚁群算法(GJAC)进行求解。最后通过数值实验验证所提算法在考虑调度优先等级及上述约束条件的同时能有效减少进离港航班队列的总延误成本。     

Displacement problem and dynamically scheduling aircraft landings

In this paper we define a generic decision problem — the displacement problem. The displacement problem arises when we have to make a sequence of decisions and each new decision that must be made has an explicit link back to the previous decision that was made. This link is quantified by means of the displacement function. One situation where the displacement problem arises is that of dynamically scheduling aircraft landings at an airport. Here decisions about the landing times for aircraft (and the runways they land on) must be taken in a dynamic fashion as time passes and the operational environment changes. We illustrate the application of the displacement problem to the dynamic aircraft landing problem. Computational results are presented for a number of publicly available test problems involving up to 500 aircraft and five runways.     

Some effects of aircraft arrival sequence algorithms

Although various airport landing sequencing algorithms have been considered in the literature, little work has been done in comparing their effects on Air Traffic Control, especially against first-come first-served (FCFS) runway sequences, the method most widely used in practice. This paper compares a number of such algorithms using a discrete-event simulation model of an airport with a single landing runway. Statistical methods are used to test for effects of sequencing algorithm, delay-sharing strategy, arrival rate and wake-vortex mix. Little benefit to delay, or stability of sequencing advice, is found from advanced sequencing when small changes are made to inputs calibrated to a specific airspace. Advanced sequencing improves landing rate, compared with FCFS sequencing, only when aircraft arrival rate is greater than maximum runway landing rate, and wake-vortex mix is sufficiently varied. Constrained position shifting constraints limit these improvements and it is shown that deterministic optimal techniques may actually be sub-optimal in a dynamic environment. Our main conclusion is that FCFS is a robust method under many conditions.     

On the waiting time of arriving aircrafts and the capacity of airports with one or two runways

In this paper we examine a model for the landing procedure of aircrafts at an airport. The characteristic feature here is that due to air turbulence the safety distance between two landing aircrafts depends on the types of these two machines. Hence, an efficient routing of the aircraft to two runways may reduce their waiting time.     

Delays to Aircraft Serviced by the Glide-Path

This paper considers some of the statistical service, flow and delay problems which arriving aircraft encounter in the glide-path of an airport runway. Mathematical expressions for service time distributions and delays are formulated in terms of the probability distributions of spacings between discharges of the glide-path. In this paper the author also considers some numerical solutions of the average glide-path separation as a function of \(\overline{w}\), the average delay to arriving aircraft, x₀, a minimum glide-path separation and λ the average Poisson flow rate of landing aircraft.     

Airport runway scheduling

Airport runway optimization is an ongoing challenge for air traffic controllers. Since demand for air-transportation is predicted to increase, there is a need to realize additional take-off and landing slots through better runway scheduling. In this paper, we review the techniques and tools of operational research and management science that are used for scheduling aircraft landings and take-offs. The main solution techniques include dynamic programming, branch and bound, heuristics and meta-heuristics.     

A combined statistical approach and ground movement model for improving taxi time estimations at airports

With the expected continued increases in air transportation, the mitigation of the consequent delays and environmental effects is becoming more and more important, requiring increasingly sophisticated approaches for airside airport operations. Improved on-stand time predictions (for improved resource allocation at the stands) and take-off time predictions (for improved airport-airspace coordination) both require more accurate taxi time predictions, as do the increasingly sophisticated ground movement models which are being developed. Calibrating such models requires historic data showing how long aircraft will actually take to move around the airport, but recorded data usually includes significant delays due to contention between aircraft. This research was motivated by the need to both predict taxi times and to quantify and eliminate the effects of airport load from historic taxi time data, since delays and re-routing are usually explicitly considered in ground movement models. A prediction model is presented here that combines both airport layout and historic taxi time information within a multiple linear regression analysis, identifying the most relevant factors affecting the variability of taxi times for both arrivals and departures. The promising results for two different European hub airports are compared against previous results for US airports.     

Airport runway scheduling

Airport runway optimization is an ongoing challenge for air traffic controllers. Since demand for air-transportation is predicted to increase, there is a need to realize additional take-off and landing slots through better runway scheduling. In this paper, we review the techniques and tools of operational research and management science that are used for scheduling aircraft landings and take-offs. The main solution techniques include dynamic programming, branch and bound, heuristics and meta-heuristics.     

A model for designing the meteorologically most reliable airline schedule

Due to meteorological conditions certain airports in some regions have to be frequently closed during winter months. An immediate consequence is an increase in the number of cancelled flights, which is a disruption of airline schedules on the overall transportation network. In this paper a research concerning the reliability of airline scheduling as related to meteorological conditions is conducted and an indicator for quantifying the adaptability of airline schedules to meteorological conditions is proposed. A heuristic algorithm for minimizing the number of needed aircraft for given traffic volume is also presented. In case where more than one solution with the same number of engaged aircraft is possible the solution chosen is the one with the minimum number of passengers whose flights are expected to be cancelled on account of meteorological conditions. The proposed algorithm is illustrated by an appropriate numerical example.     

求解带有时间窗和提前/拖期惩罚的飞机着陆问题的遗传算法

研究了带有时间窗、飞机着陆的总提前/拖期惩罚最小为目标函数的飞机着陆问题。针对此问题设计了一种遗传算法进行求解。染色体表示为飞机着陆次序和着陆跑道两个向量,一个新的解码算法来计算飞机的着陆时间。采用数据库OR-Library中的实例进行数值实验,实验结果表明：设计的算法是有效的, 主要原因是解码算法能大大提高解的质量。该算法对于求解带有时间窗、目标函数为提前/拖期惩罚最小的调度问题具有借鉴意义。     

Network design: taxi planning

The effect of managing aircraft movements on the airport’s ground is an important tool that can alleviate the delays of flights, specially in peak hours or congested situations. Although some strategic design decisions regarding aeronautical and safety aspects have a main impact on the airport’s topology, there exists a number of other additional factors that must be evaluated according to the on ground operations, i.e. previous to the taking-off or after landing. Among these factors one can consider capacities at waiting points and directions of some corridors. These factors are related to the demand situation of a given period and influence the aircraft’s routing on the ground or short term Taxi Planning problem (or TP-S). While the TP-S problem studies the aircraft routing and scheduling on the airport’s ground under a dynamic point of view, this paper presents a Taxi Planning network design model (or TPND), attending to these additional factors of the airport’s topology and the conflicting movements of the aircraft on them with the same modelling approach used in the TP-S problem. The TPND model is formulated as a binary multicommodity network flow problem with additional side constraints under a multiobjective approach. The side constraints included are the classical limitations due to capacity and also as a distinctive approach, constraints that restrict the interference of aircraft in order to decrease the intervention of human controllers during the operations or increase their safety margins. The multiobjective approach adopted for the TPND model balances conflicting objectives: airport’s throughput, travel times, safety of operations and costs. In the paper computational results are included on two test airports solving the TPND model by “Branch and Bound” showing the effect of the conflicting objectives in the design decisions. Research supported under Research Project TRA-2005-09068-C03-01/MODAL from the “Ministerio de Educación y Ciencia”.     

A theoretical model of honeycomb material arresting system for aircrafts

Takeoff and landing overruns account for most of the accidents that occur on or in the immediate vicinity of the runway, and it would cause accidental aircraft damage and loss of life. The current Engineered Material Arresting System (EMAS) materials are weak in water resistance and durability, expensive in acquiring and installing, and have negative environmental impacts. So it is significantly required to find a new alternative material with good mechanical properties, higher arresting coefficient and excellent environmental performance. In this article, the arresting properties of metal honeycomb material are studied. A Tire-Honeycomb material Interaction Mechanical Model (THIMM) is proposed. Combining with the dynamic model of aircraft, the theoretical model is coded by MATLAB to finish arresting simulation on aircraft B737-900ER and B727-100. In addition, finite element model of the tire-honeycomb material interaction was built to verify the correctness of the theoretical model. The results obtained by finite element simulation are in a good agreement with the theoretical results. In comparison with the results for traditional materials, the calculated results show that the honeycomb material can stop the overrunning aircraft more efficiently in the condition that the forces induced by the stopping process are safe for the passengers and aircraft.     

Digital Simulations of Runway Utilization

Queues of aircraft that form at airports, both in the air and on the ground, are the biggest source of delay in civil air transport operations. The study of these queues is complicated by the fact that the times at which aircraft join the queues are not independent, and also by considerable diurnal fluctuation of traffic.This paper describes an approach, primarily through simulation of idealized models, on a digital computer. The object of the work was to obtain insight into the behaviour of runway queues rather than to imitate the activity of a particular airport. The models used assume that the arrival times at the queues are the result of a scheduled pattern being disordered through aircraft being independently early or late. Such an arrival process degenerates to a Poisson process if the discrepancies from schedule are very large, but in practice it is significantly different. Results from 300,000 simulated take-offs and landings are given.     

A Simulation Model for Calculating Annual Congestion Delay Arising from Airport Runway Operations

This paper describes a simulation model of delays to aircraft caused by airport runway congestion. It was developed for the Australian Government as part of the Sydney Airport Project. Subsequently, it was used in a traffic management study of the airport which examined the scope of deferring the need for additional runway capacity by adopting administrative measures affecting runway utilization.     

Airport noise modelling and aircraft scheduling so as to minimize community annoyance

A mathematical model of the annoyance created at an airport by aircraft operations is developed. The model incorporates population distribution considerations around an airport and the annoyance caused by aircraft noise. The objective function of this model corresponds to seeking to minimize total population annoyance created by all aircraft operations in a 24-hour period. Several factors are included in this model as constraint relationships. Aircraft operations by type and time period are upper bounded. Demand for flight services is incorporated by including lower bounds on the number of operations by type of aircraft, runway used and time period. Also upper bounds on the number of operations for each runway are included. The mathematical model as formulated is recognized as corresponding to a nonlinear integer mathematical programming problem.The solution technique selected makes use of a successive linear approximation optimization algorithm. An especially attractive feature of this solution algorithm is that it is capable of obtaining solutions to large problems. For example, it would be feasible to attempt the solution of problems involving several thousand variables and over 500 linear constraints. This suggested solution algorithm was implemented on a computer and computational results obtained for example problems.     

How Airlines and Airports Recover from Schedule Perturbations: A Survey

The explosive growth in air traffic as well as the widespread adoption of Operations Research techniques in airline scheduling has given rise to tight flight schedules at major airports. An undesirable consequence of this is that a minor incident such as a delay in the arrival of a small number of flights can result in a chain reaction of events involving several flights and airports, causing disruption throughout the system. This paper reviews recent literature in the area of recovery from schedule disruptions. First we review how disturbances at a given airport could be handled, including the effects of runways and fixes. Then we study the papers on recovery from airline schedule perturbations, which involve adjustments in flight schedules, aircraft, and crew. The mathematical programming techniques used in ground holding are covered in some detail. We conclude the review with suggestions on how singular perturbation theory could play a role in analyzing disruptions to such highly sensitive schedules as those in the civil aviation industry.     

Scheduling aircraft landings at London Heathrow using a population heuristic

With increasing levels of air traffic, making effective use of limited airport capacity is obviously important. This paper reports on an investigation undertaken by National Air Traffic Services in the UK into improving runway utilisation at London Heathrow. This investigation centred on developing an algorithm for improving the scheduling of aircraft waiting to land. The heuristic algorithm developed (a population heuristic) is discussed and results presented using actual operational data relating to aircraft landings at London Heathrow. This data indicates that our algorithm could have improved on air traffic control decisions in such cases by between 2–5?% in terms of reducing the timespan required to land all of the aircraft considered.     

Experimental investigation of the effect of aircraft trailing vortices on roofs

Roofs of buildings in the vicinity of airports can be damaged by trailing vortices of aircraft during take-off and landing. Preliminary experimental investigations have been conducted in a water towing tank in order to examine a discrepancy between damage probability assumptions and actual roof damage frequency. (© 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)