Reliable and robust scheduling of airport operation resources by simulation optimization feedback and conflict resolution

Reliable and robust airport flight ground service resources collaborative scheduling has emerged as an issue of major concern at congested airports, which has great significance on airport service quality and operation efficiency. Due to the uncertainty of the service process of multiple vehicles in airport ground operations, the combination of simulation and optimization (sim-opt) techniques has been proven to be an effective means to solve the collaborative scheduling problem. However, existing models still have limitations on the reliability of feasible solutions and the robustness of evaluations. In this work, we developed a conflict resolution based sim-opt framework that combines the search capability of mathematical optimization models with the ability of simulation models to describe uncertainty. The dynamic window is introduced to divide the flight zone into multiple sub-intervals, which allows for iterative search and evaluation of the optimal schedule solution while reducing model calculation time. Additionally, a matching algorithm based on slack and tight constraints is proposed to optimize the possible resource requirements of each vehicle, thereby improving the initial schedule solution's search depth and reliability. Furthermore, a conflict resolution feedback mechanism between adjacent windows is constructed to optimize the scheduling plan, reducing misjudgment and omission of the optimal solution and enhancing the sim-opt framework's robustness. Finally, experiments on real airport datasets of three different scales demonstrate that our proposed method efficiently allocates resources with a smaller flight delay time as well as reducing total vehicle cost time during the flight ground service process.