task 1

Task 1 consists of the development of a multi-objective optimization model to determine the most efficient allocation of slots at an airport taking into account the IATA guidelines and other constrains. The model will be formulated as a mixed-integer programming (MILP) model.

The key objectives to include in the objective function of the model are the minimization of the number of flights rejected (i.e., flights for which no slots are available) and the minimization of the average time difference between the allocated slots and the requested slots. These essentially are objectives of the airlines, which aim to have their flights allocated as close as possible to the requested slots. Other objectives may also be included in the model in order to account for the perspectives of other slot allocation stakeholders. For instance, airports typically aim to maximize their profits by giving priority to flights made by larger aircraft, and travelers are mainly concerned with having frequent flights preferably to high demand destinations. We will develop a multi-criteria optimization architecture that will quantify the Pareto-efficient trade-off between these different objectives.

The decision variables of the model correspond to the slot allocation decisions that need to be made by the slot coordination entities. They provide information about the allocated slot times, in particular the time displacement of each flight in relation to the requested time and the flights that are not allocated due to limited airport capacity.

The parameters of the model, or model inputs, come from three types of data sources: (1) data from airports, about their operational and regulatory constraints, such as the declared capacity and the noise restrictions; (2) data from airlines, about their slot requests and about flight characteristics (aircraft type, connecting time, etc.); and (3) data from slot coordination entities, about the level of priority for each series of slots requested by airlines.

The model will be subjected to a set of constraints aiming to ensure that the slot allocation decisions provided by the model are fully compliant with the operational and regulatory constraints of the airport under analysis. For instance, these constraints will ensure that the runway, apron and terminal capacities are never exceeded under the schedule of flights considered. In addition, they need to maintain minimum aircraft turnaround times, that is, sufficient time to connect between the arrival of each aircraft and its departure.

Finally, in order to take into account the IATA priorities, the model will be solved hierarchically for each priority class (1. historic slots; 2. change-to-historic slots; 3. new entrant slots; 4. remaining slots). The capacity of each airport element (runway, apron, terminal) will be updated after the allocation of slots to each priority class.