Airline ground operations: Optimal schedule recovery with uncertain arrival times. (May 2021)

• Record Type: Journal Article
• Authors: Evler, Jan; Asadi, Ehsan; Preis, Henning; Fricke, Hartmut
• Is Part Of: Journal of air transport management. Volume 92(2021)
• Publication Date: 2021-05
• Subjects: Decision support system -- Airline ground operations -- Aircraft turnaround -- Schedule recovery -- Robust decision-making -- Uncertainty; Airlines -- Management -- Periodicals; Aeronautics, Commercial -- Management -- Periodicals; 387.7068
• DOI: 10.1016/j.jairtraman.2021.102021
• Languages: English
• ISSNs: 0969-6997

Abstract

Abstract: Airline operations are subject to a number of stochastic influences which result into variable ground and block times for same flights on different days. Our research explores how airline operations control centers may benefit from an integrated decision support system for schedule recovery during aircraft ground operations. In this paper, we study the sensitivity of an optimal set of schedule recovery options towards uncertain arrival times. The calculation of recovery options is based upon an integrated and iterative scheduling and optimization algorithm, which incorporates uncertainties for arrival flights as a function of a given look-ahead time. Potential recovery options include stand re-allocation, quick-turnaround, quick passenger transfer, waiting for transfer passengers, cancellation of passenger or crew connections, and arrival prioritization. Within a case study setting at Frankfurt Airport, 20 aircraft turnarounds are analysed during a morning peak with their respective estimated arrival times (including potential arrival delays). The analysis of simulation results reveals an almost identical set of selected recovery options under high uncertainty circumstances and from post-operational point-of-view, which indicates high solution stability. Highlights: Decision support framework standardizes recovery in airline hub control center. RCPSP method incorporates adaptive and restorative resilience capacities. Airline schedule recovery model considers uncertain arrival time predictions. Rolling horizon algorithm analyses robustness of recovery decisions. Case study analyses 20 parallel aircraft turnarounds at Frankfurt Airport.