Coping with Uncertainties in Predicting the Aircraft Turnaround Time at Airports.

Predicting the target time of an aircraft turnaround is of major importance for the tactical control of airport and airline network operations. Nevertheless, this turnaround time is subject to many random influences, such as passenger behavior while boarding, resource availability, and short-noticed maintenance activities. This paper proposes a mathematical optimization model for the aircraft turnaround problem while considering various uncertainties along the process. The proposed method is acting on a microscopic, thus detailed operational level. Dealing with uncertainties is implemented by two approaches. First, an analytical procedure based on convolution, which has not been considered in the literature so far but provides fast computational results, is proposed to estimate the turnaround finalization, called Estimated Off-Block Time (EOBT). The convolution algorithm considers all process-related stochastic influences and calculates the probability that a turnaround can be completed within the pre-set target time TOBT. At busy airports, such assessments are needed in order to comply with installed slot allocation mechanisms. Since aircraft turnaround operations reflect a scheduling problem, a chance-constrained MIP programming model is applied as a second approach. This procedure assumes stochastic process durations to determine the best alternative of variable process executions, so that the TOBT can be met. The procedure is applied to an Airbus A320 turnaround.