Preemptive rerouting of airline passengers under uncertain delays

Abstract

An airline's operational disruptions can lead to flight delays that in turn impact passengers, not only through the delay itself but also through possible missed connections. Much research has been done on crew recovery (rescheduling crews after a flight delay or cancellation), but little research has been done on passenger reaccommodation. Our goal is to design ways that passenger reaccommodation can be improved so that passengers can spend less time delayed and miss fewer connections. Since the length of a delay is often not known in advance, we consider preemptive rerouting of airline passengers before the length of the delay is known. Our goal is to reaccommodate passengers proactively as soon as it is known that a flight will be delayed instead of waiting until passengers have missed connections and to use known probabilities for the length of delay. In addition, we consider all of the affected passengers together so that we can effectively handle passengers' competition for available seats. We can give certain seats to people with short connections or those connecting to international flights. When there is one delayed flight, we model the problem as a two-stage stochastic programming problem, with first-stage decisions that assign passengers initial xi itineraries and second-stage decisions that reassign any passengers who are subsequently disrupted by the delay. We present a Benders decomposition approach to solving this problem. Computational results for this model are given, showing its effectiveness for reducing the length of passenger delays. When there is more than one delayed flight, we define a portfolio model which assigns passengers to portfolios that define their itineraries under all possible disruption outcomes. We focus on computational methods for solving this model. xii

A mathematical model for integrated aircraft and crew recovery after a disruption: a Benders’ decomposition approach

“…Jafari and Zegordi (2011) developed an integrated mixed integer model for aircraft and passenger recovery JM2 18,6 based on Abdelghany (2008) model with independent flight resources. McCarty (2012) introduced a multi stage approach that offered possible improved routes for passenger recovery by identification of passenger itinerary. As a matter of fact, when a delay happens in one or more scheduled flights, passengers experience less dissatisfaction about their itinerary changes.…”

“…As a matter of fact, when a delay happens in one or more scheduled flights, passengers experience less dissatisfaction about their itinerary changes. McCarty and Cohn (2018) proposed a two-stage stochastic programming model to passengers preemptive rerouting under uncertain delays. They used Benders’ decomposition algorithm as a solution approach.…”

“…Also, Petersen et al (2012) applied Benders’ decomposition algorithm for recovery problem. McCarty and Cohn (2018) used Benders’ decomposition algorithm to solve the passenger recovery problem in reasonable computation time. In a state of the art, Rahmaniani et al (2017) referred to the features and widespread applications of this technique.…”

Dynamic Disruption Management in Airline Networks Under Airport Operating Uncertainty

“…Jafari and Zegordi (2010) dynamically optimize aircraft recovery and passenger re-accommodation, on a relatively small-scale network and with two disruption scenarios. McCarty and Cohn (2018) propose a two-stage stochastic program to pre-emptively change passenger itineraries, before misconnections occur, under uncertainty on delay propagation. Our paper shares similarities with this approach but also exhibits two differences: (i) we focus on aircraft recovery, as opposed to passenger recovery, and (ii) we incorporate forecasts of propagated delays as well as systemic delays resulting from airport congestion.…”

Evolutionary framework for two-stage stochastic resource allocation problems

“…Airline operations: McCarty & Cohn (2018) propose a model for the decision-making of anticipating passenger reaccommodation from delayed flights. The first-stage decisions assign passengers to new itineraries in anticipation of the delay's impact and second-stage decisions adjust itineraries for passengers who missed their connections once the delay has been realized.…”