Edmund K. Burke

Hybrid Metaheuristics to Aid Runway Scheduling at London Heathrow Airport

Although London Heathrow is one of the busiest airports in the world, it has only one runway for use by departing aircraft at any time. Separations are required between each pair of aircraft at take-off---depending on their routes, weights, and speeds---to ensure safety. Efficient scheduling of the aircraft for take-off can reduce the total separations and increase throughput. A runway controller is responsible for take-off scheduling. This is a very intensive job with responsibility for all communication with aircraft and continuous monitoring to assure safety. The high workload limits the number of aircraft that the controller can take account of when scheduling. The geometry of the runway holding points adds physical constraints to the reordering of aircraft that are usually ignored in the academic literature. We present models for evaluating a schedule and determining the effects of the physical constraints. We propose a hybrid metaheuristic system that takes account of more aircraft than a human controller can handle, and so can aid the runway controller by recommending schedules that anticipate some future problems. We present results to show the effectiveness of this system, and we evaluate those results against real-world schedules.

A multi-objective approach for robust airline scheduling

We present a memetic approach for multi-objective improvement of robustness influencing features (called robustness objectives) in airline schedules. Improvement of the objectives is obtained by simultaneous flight retiming and aircraft rerouting, subject to a fixed fleet assignment. Approximations of the Pareto optimal front are obtained by applying a multi-meme memetic algorithm. We investigate biased meme selection to encourage exploration of the boundaries of the search space and compare it with random meme selection. An external population of high quality solutions is maintained using the adaptive grid archiving algorithm. The presented approach is applied to investigate simultaneous improvement of reliability and flexibility in real world schedules from KLM Royal Dutch Airlines. Experimental results show that the approach enables us to obtain schedules with significant improvements for the considered objectives. A large scale simulation study was undertaken to quantify the influence of the robustness objectives on the operational performance of the schedules. Rigorous sensitivity analysis of the results shows that the influence of the schedule reliability is dominant and that increased schedule flexibility could improve the operational performance.

On-line decision support for take-off runway scheduling with uncertain taxi times at London Heathrow airport

This paper addresses the challenge of building an automated decision support methodology to tackle the complex problem faced every day by runway controllers at London Heathrow Airport. Aircraft taxi from stands to holding areas at the end of the take-off runway where they wait in queues for permission to take off. A runway controller attempts to find the best order for aircraft to take off. Sequence-dependent separation rules that depend upon aircraft size, departure route and speed group ensure that this is not a simple problem to solve. Take-off time slots on some aircraft and the need to avoid excessive delay for any aircraft make this an even more complicated problem. Making this decision at the holding area helps to avoid the problems of unpredictable push-back and taxi times, but introduces a number of complex spatial constraints that would not otherwise exist. The holding area allows some flexibility for interchange of aircraft between queues, but this is limited by its physical layout. These physical constraints are not usually included in academic models of the departure problem. However, any decision support system to support the take-off runway controller must include them. We show, in this paper, that a decision support system could help the controllers to significantly improve the departure sequence at busy times of the day, by considering the taxiing aircraft in addition to those already at the holding area. However, undertaking this re-introduces the issue of taxi time uncertainty, the effect of which we explicitly measure in these experiments. Empirical results are presented for experiments using real data from different times of the day, showing how the performance of the system varies depending upon the volume of traffic and the accuracy of the provided taxi time estimations. We conclude that the development of a good taxi time prediction system is key to maximising the benefits, although benefits can be observed even without this.

A more realistic approach for airport ground movement optimisation with stand holding

In addition to having to handle constantly increasing numbers of aircraft, modern airports also have to address a wide range of environmental regulations and requirements. As airports work closer and closer to their maximal possible capacity, the operations problems that need to be solved become more and more complex. This increasing level of complexity leads to a situation where the introduction of advanced decision support systems becomes more and more attractive. Such systems have the potential to improve efficient airside operations and to mitigate against the environmental impact of those operations. This paper addresses the problem of moving aircraft from one location within an airport to another as efficiently as possible in terms of time and fuel spent. The problem is often called the ground movement problem and the movements are usually from gate/stands to a runway or vice-versa. We introduce a new sequential graph based algorithm to address this problem. This approach has several advantages over previous approaches. It increases the realism of the modelling and it draws upon a recent methodology to more accurately estimate taxi times. The algorithm aims to absorb as much waiting time for delay as possible at the stand (with engines off) rather than out on the taxiways (with engines running). The impact of successfully achieving this aim is to reduce the environmental pollution. This approach has been tested using data from a European hub airport and it has demonstrated very promising results. We compare the performance of the algorithm against a lower bound on the taxi time and the limits to the amount of waiting time that can be absorbed at stand.

The trade-off between taxi time and fuel consumption in airport ground movement

Environmental issues play an important role across many sectors. This is particularly the case in the air transportation industry. One area which has remained relatively unexplored in this context is the ground movement problem for aircraft on the airport’s surface. Aircraft have to be routed from a gate to a runway and vice versa and a key area of study is whether fuel burn and environmental impact improvements will best result from purely minimising the taxi times or whether it is also important to avoid multiple acceleration phases. This paper presents a newly developed multi-objective approach for analysing the trade-off between taxi time and fuel consumption during taxiing. The approach consists of a combination of a graph-based routing algorithm and a population adaptive immune algorithm to discover different speed profiles of aircraft. Analysis with data from a European hub airport has highlighted the impressive performance of the new approach. Furthermore, it is shown that the trade-off between taxi time and fuel consumption is very sensitive to the fuel-related objective function which is used.

A Metaheuristic Approach to Aircraft Departure Scheduling at London Heathrow Airport

London Heathrow airport is one of the busiest airports in the world. Moreover, it is unusual among the world’s leading airports in that it only has two runways. At many airports the runway throughput is the bottleneck to the departure process and, as such, it is vital to schedule departures effectively and efficiently. For reasons of safety, separations need to be enforced between departing aircraft. The minimum separation between any pair of departing aircraft is determined not only by those aircraft but also by the flight paths and speeds of aircraft that have previously departed. Departures from London Heathrow are subject to physical constraints that are not usually addressed in departure runway scheduling models. There are many constraints which impact upon the orders of aircraft that are possible and we will show how these constraints either have already been included in the model we present or can be included in the future. The runway controllers are responsible for the sequencing of the aircraft for the departure runway. This is currently carried out manually. In this paper we propose a metaheuristic-based solution for determining good sequences of aircraft in order to aid the runway controller in this difficult and demanding task. Finally some results are given to show the effectiveness of this system and we evaluate those results against manually produced real world schedules.

Addressing the Pushback Time Allocation Problem at Heathrow Airport

This paper considers the problem of allocating pushback times to departing aircraft, specifying the time at which they will be given permission to push back from their allocated stand, start their engines, and commence their taxi to the runway. The aim of this research is to first predict the delay (defined as the waiting time at the stand or runway) for each departure, then to use this to calculate a pushback time such that an appropriate amount of the delay is absorbed at the stand, prior to starting the engines. A two-stage approach is used, where the feasibility of the second stage (pushback time allocation) has to be considered within the first stage (takeoff sequencing). The characteristics of this real-world problem and the differences between it and similar problems are thoroughly discussed, along with a consideration of the important effects of these differences. Differences include a nonlinear objective function with a nonconvex component; the integration of two sequence dependent separation problems; separations that can vary over time; and time-slot extensions. Each of these factors has contributed to the design of the solution algorithm. Results predict significant fuel-burn benefits from absorbing some of the delay as stand hold, as well as delay benefits from indirectly aiding the runway controllers by reducing runway queue sizes. A system for pushback time allocation at London Heathrow has been developed by NATS (formerly National Air Traffic Services) based upon the algorithm described in this paper.

An examination of take-off scheduling constraints at London Heathrow airport

In this paper, we focus upon the departure system for London Heathrow airport, one of the busiest airports in the world. Decreasing the delay for aircraft awaiting take-off with their engines running would decrease fuel usage and have consequent cost and pollution benefits. We explain how the departure system at Heathrow currently works and we describe the various constraints that apply to take-off schedules. A model for the take-off order problem is presented from the point of view of the runway controller, the person who is responsible for the take-off scheduling. We investigate the effects of each constraint and combination of constraints, using a simulation of the Heathrow departure system. The role of the runway controller in the simulation is performed by a search which was designed to form the basis of an online decision support system. Both the simulation and the decision support system are fully described. We use the results to evaluate the effect upon delay that we would expect from various changes that could be made to the departure system. We end the paper by drawing conclusions about the predicted effectiveness of different changes that could be made to the departure system and focus upon a further opportunity for decision support research.

A comparison of two methods for reducing take-off delay at London Heathrow airport

This paper describes recent research into the departure process at London Heathrow, with the primary motivation of reducing the amount of fuel used, improving both the economic and environmental costs. Two proposals are considered here. The first proposal considers the practicality and potential benefits of aiding the controller in improving the take-off sequencing. The second proposal aims to absorb some of the inevitable delay for aircraft at the stands, before the engines are started, but also involves a take-off sequencing aspect. Models for the two take-off sequencing problems are presented in this paper, the second of which includes an additional pushback time (or TSAT) allocation sub-problem which has to be solved subsequently. These models have distinctive differences from the models for the take-off and arrival sequencing problems which are usually considered in the literature, since they take into account necessary constraints imposed due to the control problem (whether a sequence can actually be achieved, and how) in each case. As discussed in this paper, the control problem cannot be ignored by the controllers at Heathrow, and so it cannot be ignored by any realistic system to aid them in their tasks. Comparative take-off sequencing results are presented for the two systems, and the potential benefits from providing decision support to the runway controllers or improved TSAT allocation at the stands are considered. The paper ends with some overall conclusions from the research, showing the large potential benefits of these systems. The TSAT allocation system which is discussed in this paper has been developed for implementation at London Heathrow as one element of a major project which focuses upon collaborative decision making.