Mathematical models and algorithms for allocating scarce airport resources (OR-MASTER)

Congestion at major airports in the UK and across Europe and the rest of the world is a serious and growing problem. Already Heathrow faces problems occasioned by serious congestion for a major part of the day while at Gatwick demand is expected to exceed capacity for 17 hours per day by 2025. According to a Eurocontrol study, planned capacity at the 138 Eurocontrol Statistical Reference Area (ESRA) airports is expected to increase by 41% in total by 2030, with demand exceeding airport capacity by as much as 2.3 million flights (or 11%) in the most-likely forecast growth scenario.

The development and deployment of airport capacity is a major societal issue engendering intense public debate in the UK and around the world.
Capacity at congested airports is expressed in slots. A slot identifies a time interval on a specific date during which a carrier is permitted to use the airport infrastructure for landing or take-off. Current slot allocation procedures suffer (inter alia) from the following limitations:

1)Simplistic modelling of the objectives and operational/regulatory constraints bearing on the multiple stakeholders involved in (and affected by) the slot allocation process.

2)Insufficient capture of the interactions encountered in airport networks.

3)The use of empirical or ad hoc processes for determining (rather than computing) declared capacity which address neither the uncertainties involved in airport capacity assessment nor the complexity and size of the real-world problem, even at the single-airport level.

Consequently, existing approaches to the allocation of airport capacity fail in a number of critical ways to reflect the complexities presented by the real world. This creates allocation inefficiencies which, in turn, result in poor airport capacity utilisation with significant negative impacts on airport revenues, airline operating costs, the level of service offered to passengers and the environment.

There is thus a pressing need to meet the major scientific challenge of developing novel mathematical models and solution approaches to transform the airport slot allocation process and its associated outcomes. The programme grant aims to do just that for a single airport and for a network of airports. Mathematical models will be developed and analysed which consider the objectives and requirements of all stakeholders and which take account of a wide range of operational and regulatory constraints. The intrinsic complexity of the proposed programme and its large scale (especially for the case of the network-wide slot allocation) will mean that it will provide an excellent test-bed for the development of new heuristics and hyper heuristics for large scale complex scheduling problems more widely. Algorithms that will be developed and tested by this project will provide essential support for the complex large scale capacity allocation problems that arise in other types of transportation networks, including rail networks. In addition, it could extend to other types of networks that share similar problem structures, such as those in energy and telecommunications.

The models and solution techniques developed will underpin the development of novel decision support systems which have the potential to make a major impact on airport operations. The research team has an internationally leading profile in the areas of mathematical modelling, heuristic development, stochastic optimization, airport slot allocation, airport management and performance assessment. It has an excellent track record of research cooperation with all categories of stakeholders. It will cooperate closely with an impressive array of leading industry stakeholders in order to make sure that the work is as cutting edge industrially as it is scientifically.

This proposal is addressing an issue of great societal and scientific concern. It will have significant impact on i) the air transport industry, ii) policy makers and government, iii) associated scientific communities, iv) research training and v) the general public.

In what follows, we provide an overview of some of the key potential impacts of the proposed research programme on each of these stake-holding groups.

(i) Air Transport Industry: The optimization of slot allocation will bring major benefit to airports, the airline industry, and providers of air traffic and ground handling services. All of these industry sectors will benefit from the improved utilization of airport capacity which will result from improved slot allocation. The models and algorithms that will be developed will help air transport industry decision makers to reduce delays, increase schedule reliability, decrease operating costs, and increase revenues.

(ii) Policy Makers and Government: The results of the proposed programme will support decision makers to manage efficiently the available airport infrastructure and to improve the allocation of financial and other resources for developing additional capacity. The proposed programme will thus impact on issues of airport capacity management and development which are of central importance to the UK Government and across Europe.

(iii) Associated Scientific Communities: The proposed programme will have significant impact on the advancement of knowledge in a field that cuts across several scientific communities including operations research, mathematics, management science, computer science, air transport and engineering. It addresses challenges that lie at the interfaces of these fields. This programme will contribute substantially to our mathematical understanding of the modelling of complex large scale systems. It will also contribute to the development and theoretical understanding of innovative adaptive search methods for solving scheduling problems under uncertainty.

(iv) Research Training: This Programme Grant will provide a unique and valuable research training environment for our research associates and PhD students. They will have the opportunity to engage closely with international research centres and air transport industry organizations through short term visits and secondments. This international exchange and industrial exposure will underpin their inter-disciplinary research training experience.

(v) General Public: This programme has the potential to generate significant social, economic, and environmental impact. The development of models and systems for improved airport capacity management will substantially decrease congestion and reduce delays for the travelling public. Further, airport congestion generates a negative impact on air pollution, aircraft noise and safety, while delays cause significant economic damage. For example, related studies in the USA have estimated that the total economic impact of air transportation delays on the US economy for 2007 was $28.9 billion.