Flight gate assignment and recovery strategies with stochastic arrival and departure times

We consider the problem of assigning flights to airport gates. We examine the general case in which an aircraft serving a flight may be assigned to different gates for arrival, parking, and departure processing. The objectives can be divided into deterministic and stochastic goals. The former include maximization of the total assignment preference score, a minimal number of unassigned flights during overload periods, and minimization of the number of tows. A special focus lies on the stochastic objectives, which aim at minimizing the expected number of any kind of constraint violations, i.e. not respecting gate closures, violation of shadow restrictions (a situation in which gate assignments may cause blocking of neighboring gates) or of tow time restrictions and classical gate conflicts in which two aircraft are assigned to the same gate and are at the airport at the same time. We show that the minimization of expected gate conflicts can be modeled in a graph theoretical approach using the clique partitioning problem (CPP). We furthermore show that the classical (deterministic) flight gate assignment problem, which can also be modeled using a CPP, can be integrated such that a simple though powerful model emerges, which no longer needs including a dummy gate, which is often used in practical gate assignment models. As constraint violations cannot fully be prevented, recovery strategies become necessary. We present a procedure for recovery planning that has proved its practical relevance at numerous airports. Finally, in an extensive numerical study we test our results on practical data, which contain a statistical analysis of flight arrival and departure times. The tests include a detailed comparison of current robustness measures and state-of-the-art approaches found in literature.