Airline-driven ground delay programs: A benefits assessment. (April 2018)

• Record Type: Journal Article
• Authors: Yan, Chiwei; Vaze, Vikrant; Barnhart, Cynthia
• Is Part Of: Transportation research. Volume 89(2018)
• Page Start: 268
• Page End: 288
• Publication Date: 2018-04
• Subjects: Ground delay programs -- Air traffic flow management -- Collaborative decision making -- Airline recovery operations; Transportation -- Periodicals; Transportation -- Technological innovations -- Periodicals; 388.011
• DOI: 10.1016/j.trc.2018.02.013
• Languages: English
• ISSNs: 0968-090X

Abstract

Highlights: Airlines differ significantly in their preferences and responses to GDP designs. An airline-driven GDP design reduces total costs compared to a centralized design. An airline-driven approach also distributes benefits more equitably across airlines. Abstract: Three decades of research studies in ground delay program (GDP) decision-making, and air traffic flow management in general, have produced several analytical models and decision support tools to design GDPs with minimum delay costs. Most of these models are centralized, i.e., the central authority almost completely decides the GDP design by optimizing certain centralized objectives. In this paper, we assess the benefits of an airline-driven decentralized approach for designing GDPs. The motivation for an airline-driven approach is the ability to incorporate the inherent differences between airlines when prioritizing, and responding to, different GDP designs. Such differences arise from the airlines' diverse business objectives and operational characteristics. We develop an integrated platform for simulating flight operations during GDPs, an airline recovery module for mimicking the recovery actions of each individual airline under a GDP, and an algorithm for fast solution of the recovery problems to optimality. While some of the individual analytical components of our framework, model and algorithm share certain similarities with those used by previous researchers, to the best of our knowledge, this paper presents the first comprehensive platform for simulating and optimizing airline operations under a GDP and is the most important technological contribution of this paper. Using this framework, we conduct detailed computational experiments based on actual schedule data at three of the busiest airports in the United States. We choose the recently developed Majority Judgment voting and grading method as our airline-driven decentralized approach for GDP design because of the superior theoretical and practical benefits afforded by this approach as shown by multiple recent studies. The results of our evaluation suggest that adopting this airline-driven approach in designing the GDPs consistently and significantly reduces airport-wide delay costs compared to the state-of-the-research centralized approaches. Moreover, the cost reduction benefits of the resultant airline-driven GDP designs are equitably distributed across different airlines.