(coordinators) who allocate slots for arriving and departing flights. Each airport must decide how much capacity it has – which is translated to how many slots are available, for both arrivals and departures, in an hour and sub-intervals of an hour, e.g. 15 minutes. The balance will vary during the day – at certain times, more slots will be available for flights to land than take-off, and vice-versa. Airlines then request slots for their flights. Passengers have their own preferences for when they want to fly. This affects demand for slots and their distribution in time, e.g. during the day, and throughout the days and weeks of a season. Taking into account these requests and the available capacity, coordinators allocate slots. Airlines’ requests may have to be moved by so many minutes either side of their desired slots, others will get exactly what they want. It is a mammoth task. There is a complex framework determined by international guidelines that dictates how capacity is allocated. These guidelines introduce criteria, priorities, and constraints on how the various categories of requests placed by the airlines should be accommodated. Our task has been to develop mathematical models taking into account the slot allocation decisionmaking environment, and associated solutions algorithms. We need to provide the decision-makers with information, which will lead to greater levels of efficiency, fairness, and transparency. Both airports and airlines have goals and desires, as do the air traffic control organisations who look after airspace, and there are different groups within those larger sets. For instance, the requests of airlines that have historical slot usage rights (referred to as grandfather rights) at an airport, have a priority over the requests of airlines that are seeking to enter the market. Any change to the status quo is likely to meet resistance. However, even within the existing decision-making framework changes that do not radically challenge the fundamental assumptions of this framework, i.e. grandfather rights, can bring about improvements in the quality of airport slot allocation. Discussions on potential changes have been going on for decades. It is impossible to satisfy everyone completely, though it is necessary for all stakeholders (airlines, coordinators, airports, and air traffic service providers) to agree a roadmap for the implementation of a new system. With a level of compromise, there can be benefits in certain areas for everyone. We are looking for an optimal setting of capacity and delays, at single-airport and network levels. We created models that incorporate the preferences of all stakeholders for multiple objectives. Our models can help decisionmakers to find a commonly acceptable airport schedule that balances the preferences. The mathematical models developed within the OR-MASTER project provide the capability to support a more objective decision-making process. We can provide facts and data to back-up the generated solutions. Sacrifices must be made, and the models and methodologies can show decisionmakers where this can happen most effectively while ensuring all the airlines obtain slots as close as possible to those they want. ADVANCE PLANNING Airports must declare their slot capacity six months in advance, and major scheduling decisions are made based on these levels. Airports have a maximum capacity level based on everything running smoothly. If they were to use this for scheduling purposes, they might be able to make more airlines happy by giving them the slots they want; but it is not practical. It does not allow for issues with weather or other delaying factors. There must be some slack built in for it to be workable, and to avoid major delays that deteriorate the level of service provided to the travelling public. Our research looks at the potential levels of capacity and the likely levels of delays which would result. It is about finding a schedule that considers the need of the airlines getting slots as close as possible to what they want and the need to be able to depart and arrive on time. The mathematical models we have created can help generate optimal airport schedules and shed light on the trade-offs necessary to accommodate slot allocation objectives. This means those airlines which miss out on the slots they want can see how the process works. The proposed models can be applied to coordinated airports. Each airport is an individual case and will need to appropriately set the parameters of the models reflecting their operating conditions and local needs. Our work will help to manage the demand-supply imbalance, through the optimal allocation of the available capacity. This will result in efficient schedules and will support a fairer playing field for everyone. FIFTY FOUR DEGREES | 35 Konstantinos Zografos is Distinguished Professor in the Department of Management Science, and Director of the Centre for Transport and Logistics (CENTRAL) in Lancaster University Management School. Professor Zografos leads the Engineering and Physical Sciences Research Council (EPSRC)-funded OR-MASTER (Mathematical Models and Algorithms for Allocating Scarce Airport Resources) project. Researchers at Lancaster involved in OR-MASTER include Professor Kevin Glazebrook (Co-Investigator), Dr Nihal Berktas, Dr Burak Boyaci, Dr Jamie Fairbrother, Dr Kamyar Kargar, Dr Fotios Katsigiannis, Dr Merve Keskin, Theodoti Kerama, Davood Mohammadi, Professor Stefanos Mouzas, Dr Aleksandr Pirogov, Dr Robert Shone, Dr David Torres-Sanchez, and Dr Jiang Yu. k.zografos@lacaster.ac.uk
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