Évaluation de politiques de séquençage d'arrivées d'avions par Simulation Monte Carlo
With the air traffic increase, airport runway management is becoming a critical issue both at the operational and safety levels. Runways have limited capacity and a minimum separation distance must be maintained between two consecutive aircrafts during both takeoff and landing phases due to wake turbulences. The minimum separation between two aircrafts depends on their size, influencing their sensitivity to turbulence. As a result, the ordering of takeoffs and landings affects the minimum total waiting time for a sequence of takeoffs or landings, as well as the delays imposed on passengers. Various scheduling policies have been proposed to reduce the delays, usually based on heuristics as the sequencing problem is NP hard. In addition, little attention is usually paid to the random factors influencing take-off and landing times. We focus on landings as they are more critical than takeoffs and propose a discrete event simulation tool to evaluate different landing scheduling policies, taking account of the operational constraints on separation as well as the uncertainties on the arrival times in the airport area. We then compare several popular policies, based on various measures of performance. Contrary to the usual assumption of deterministic flight durations, we consider the noise between the expected arrival time and the realized arrival time and examine the impacts on the scheduling performance.
Stochastic simulation Scheduling Discrete events Air traffic contol Aircraft landing