An Evolutionary Hyper-Heuristic for Airport Slot Allocation

A large number of airports across Europe are resource constrained. With long-term growth in air transportation forecast to rise, more airports are expected to feel the imbalance between increased demand and limited resource capacity. This imbalance will lead to increasingly constrained scenarios, which require sophisticated solution methods to produce viable schedules. The use of ‘slots’ is one of the core mechanisms for managing access to constrained resources at airports. This paper presents a genetic algorithm-based hyper-heuristic approach to construct feasible solutions to the single airport slot allocation problem. To evaluate the proposed approach, we compare the solutions found by a number of previously developed and newly proposed constructive heuristics, over a range of real-world data sets. Our results show that the hyper-heuristic outperforms any individual constructive heuristic in all test instances, overcoming the drawbacks that a single heuristic faces when required to solve instances with different problem features.