Aircraft Rescheduling with Cruise Speed Control

Abstract

Airline operations are subject to frequent disruptions typically due to unexpected aircraft maintenance requirements and undesirable weather conditions. Recovery from a disruption often involves propagating delays in downstream flights and increasing cruise stage speed when possible in an effort to contain the delays. However, there is a critical trade-off between fuel consumption (and its adverse impact on air quality and greenhouse gas emissions) and cruise speed. Here we consider delays caused by such disruptions and propose a flight rescheduling model that includes adjusting cruise stage speed on a set of affected and unaffected flights as well as swapping aircraft optimally. To the best of our knowledge, this is the first study in which the cruise speed is explicitly included as a decision variable into an airline recovery optimization model along with the environmental constraints and costs. The proposed model allows one to investigate the trade-off between flight delays and the cost of recovery. We show that the optimization approach leads to significant cost savings compared to the popular recovery method delay propagation. Flight time controllability, nonlinear delay, fuel burn and CO2 emission cost functions, and binary aircraft swapping decisions complicate the aircraft recovery problem significantly. In order to mitigate the computational difficulty we utilize the recent advances in conic mixed integer programming and propose a strengthened formulation so that the nonlinear mixed integer recovery optimization model can be solved efficiently. Our computational tests on realistic cases indicate that the proposed model may be used by operations controllers to manage disruptions in real time in an optimal manner instead of relying on ad-hoc heuristic approaches.

Robust Airline Scheduling with Controllable Cruise Times and Chance Constraints

“…We first tested our model on a problem instance used in a recent work by Aktürk et al (2014). The instance is called Single Hub Data as the flight network is formed by considering aircraft that originate their first flight from Chicago O'Hare International Airport (ORD) and revisit ORD at least once during the same day.…”

Accommodating new flights into an existing airline flight schedule

“…where ρ ≥ 0. As in Aktürk et al (5), we let ζ = 1.5 in our computational experiments. It is important to note that the US costs might differ from the ones provided in the EUROCONTROL [28].…”

“…Therefore, if a flight is delayed, swapping the aircraft provides robustness by allowing a flight with high demand to be flown. Aktürk et al [5] use the idea of swapping aircraft between flights to reduce the effect of a disruption on the schedule. They provide approximately 30% cost savings compared to the delay propagation recovery approach.…”

“…However, in the context of airline operations, this representation leads to a large number of copies of flights to be evaluated in the model. Arikan et al [6] and Aktürk et al [5] express cruise speed as a continuous variable and find an optimal trade-off between increased fuel cost and disruption costs such as delay and spilled passengers costs. To manage disruptions in a less costly manner, airlines are also interested in building robust schedules.…”

Coordination of scheduling decisions in the management of airport airspace and taxiway operations

“…An extensive overview of early contributions can be found in Ball et al (2007), while more recent surveys can be found in Barnhart et al (2012), Bianco et al (2006) and Pellegrini and Rodriguez (2013). We observe that, while the coordination issue is often referred to multi-airport coordination, as in Aktürk et al (2014) or Andreatta et al (2011), this paper focuses on coordination of operations in a single airport. In the latter context, Balakrishnan andChandran (2010), andSölveling et al (2010) focus on the runway scheduling, Artiouchine et al (2008), Hu and Chen (2005), and Di Paolo (2008,2009) focus on the landing scheduling from airspace resources to runways, while other authors deal with the coordination of the TCA airspace and the runways (landing and take-off scheduling), e.g., D'Ariano et al (2012D'Ariano et al ( , 2015, Lieder and Stolletz (2016), Murça and Müller (2015), Samà et al (2013Samà et al ( , 2014Samà et al ( , 2015.…”