Metaheuristic algorithms for the simultaneous slot allocation problem

In this paper, we propose the formalization of the simultaneous slot allocation problem (SSAP), that extends in two directions the current way of allocating airport slots in Europe. The SSAP requires, first, to perform the slot allocation at all airports simultaneously and, second, to respect airspace sector capacities. We solve the SSAP with two algorithms based on metaheuristics, namely Iterated Local Search and Variable Neighborhood Search, and with an algorithm based on an integer linear programming model. We compare these algorithms on randomly generated instances and we show that for small instances metaheuristics are competitive with the integer linear programming model. Nevertheless, the integer linear programming model is unable to solve medium or large instances due to memory and computation time requirements. Metaheuristics, instead, can deal with large instances, allocating slots to more than 99.8% of flights.