A simheuristic approach for solving the aircraft Recovery Problem with stochastic delays

Air transport operational disruptions arise when operations deviate from the original plan. Due to airlines network configuration, delays are rapidly propagated to connecting flights, substantially increasing unexpected costs for the airlines. The goal in these situations is therefore to minimise the impact of the disruption, reducing delays and the number of affected flights, crews and passengers. However, the reach of a specific disruption is not normally known or it is difficult to assess, increasing the complexity of the problem. In this work, we introduce a methodology based on a Large Neighbourhood Search metaheuristic and a Constraint Programming formulation to tackle the Aircraft
Recovery Problem with stochastic delays. We use simulation to help guiding the search, account for system’s variability, and evaluate solutions’ behaviour. We present some preliminary results on a set of instances with different sizes and characteristics, including some instances originating from real data.