Decreasing Airline Delay Propagation by Re-allocating Scheduled Slack

Passenger airline delays have received increasing attention over the past several years as airspace congestion, severe weather, mechanical problems, and other sources cause substantial disruptions to a planned flight schedule. Adding to this challenge is the fact that each flight delay can propagate to disrupt subsequent downstream flights that await the delayed flights' aircraft and crew. This potential for delays to propagate is exacerbated by a fundamental conflict: slack in the planned schedule is often viewed as undesirable, as it implies missed opportunities to utilize costly perishable resources, whereas slack is critical in operations as a means for absorbing disruption. In this paper, we show how delay propagation can be reduced by redistributing existing slack in the planning process, making minor modifications to the flight schedule while leaving the original fleeting and crew scheduling decisions unchanged. We present computational results based on data from a major U.S. carrier, showing that significant improvements in operational performance can be achieved without increasing planned costs

Analysis of the Potential for Delay Propagation in Passenger Airline Networks

In this paper, we analyze the potential for delays to propagate in passenger airline networks. The motivation for this research is the need to better understand the relationship between the scheduling of aircraft and crew members, and the operational performance of such schedules. In particular, when carriers decide how to schedule these costly resources, the focus is primarily on achieving high levels of utilization. The resulting plans, however, often have little slack, limiting the schedule's ability to absorb disruption; instead, initial flight delays may propagate to delay subsequent flights as well. Understanding the relationship between planned schedules and delay propagation is a requisite precursor to developing tools for building more robust airline plans. In this paper, we investigate this relationship using flight data provided by two major U.S. carriers, one traditional hub-and-spoke and one “low-fare” carrier

An Integer Programming Approach to Generating Airline Crew Pairings

Key Words: integer programming; column generation; crew pairing; crew scheduling; airline planning. The ability to generate crew pairings quickly is essential to solving the airline crew scheduling problem. Although techniques for doing so are well-established, they are also highly customized and require significant implementation efforts. This greatly impedes researchers studying important problems such as robust planning, integrated planning, and automated recovery, all of which also require the generating of crew pairings. As an alternative, we present an integer programming (IP) approach to generating crew pairings, which can be solved via traditional methods such as branch-and-bound using off-the-shelf commercial solvers. This greatly facilitates the prototyping and testing of new research ideas. In addition, we suggest that our modeling approach, which uses both connection variables and marker variables to capture the non-linear cost function and constraints of the crew scheduling problem, can be applicable in other scheduling contexts as well. Computational results using data from a major U.S. hub-and-spoke carrier demonstrate the performance of our approach.