Most airlines have established integrated hub and operations control centers for the monitoring and adjustment of tactical operations. However, decisions in such a control center are still elaborated manually on the basis of expert knowledge held by several agents representing the interests of different airline departments and local stakeholders. This article studies a concept which incorporates the situational awareness gained by airport-collaborative decision making into an airline-internal decision support system, such that it integrates all available schedule recovery options during aircraft ground operations. The developed mathematical optimization model is an adaptation of the Resource-Constrained Project Scheduling Problem (RCPSP) and incorporates key features from turnaround target time prediction, passenger connection management, tactical stand allocation and ground service vehicle routing into the airline hub control problem. The model is applied in a case study consisting of 20 turnarounds during a morning peak at Frankfurt airport. Schedule recovery performance (resilience) is analyzed for a set of key performance indicators within multiple scenario instances which contain different resource availability and aim at solving various arrival delay situations. Results highlight that a minimization of tactical cost concurrently reduces average departure delay for flight and passengers while recovery performance is substantially affected when some options are not included in the evaluation process. Thus, our concept provides airlines with an optimization approach for constrained airport resources so that total cost and delay resulting from schedule deviations are reduced, which may benefit strategic schedule planning and improve predictability of operations for local collaborators, such as airport, ground handlers and ATM performance.

大多数航空公司都建立了集成的枢纽和运营控制中心，以监控和调整战术运营。但是，仍会根据代表不同航空公司部门和当地利益相关者利益的几个代理商所掌握的专业知识，手动制定此类控制中心的决策。本文研究了一种概念，该概念将机场协作决策中获得的态势感知整合到航空公司内部的决策支持系统中，从而将飞机地面运营过程中的所有可用时间表恢复选项进行了整合。开发的数学优化模型是对资源受限的项目计划问题（RCPSP）的改编，并结合了以下目标的关键功能：周转目标时间预测，乘客接驳管理，战术展位分配和地面服务车辆路线转换成航空公司枢纽控制问题。该模型应用于案例研究，该案例研究包括在法兰克福机场的一个早晨高峰期进行的20次周转。针对包含不同资源可用性并旨在解决各种到达延迟情况的多个场景实例中的一组关键性能指标，分析了计划恢复性能（恢复力）。结果表明，最小化战术成本同时减少了航班和乘客的平均离港延误，而当评估过程中未包括某些选项时，恢复性能将受到重大影响。因此，我们的概念为航空公司提供了一种针对受限机场资源的优化方法，从而减少了因航班时刻表偏差而导致的总成本和延误，